diff --git a/sdk/ai/Azure.AI.Inference/src/Generated/AIInferenceClientBuilderExtensions.cs b/sdk/ai/Azure.AI.Inference/src/Generated/AIInferenceClientBuilderExtensions.cs
index b164a88148d3..3348bd6a13c2 100644
--- a/sdk/ai/Azure.AI.Inference/src/Generated/AIInferenceClientBuilderExtensions.cs
+++ b/sdk/ai/Azure.AI.Inference/src/Generated/AIInferenceClientBuilderExtensions.cs
@@ -12,89 +12,35 @@
 
 namespace Microsoft.Extensions.Azure
 {
-    /// <summary> Extension methods to add <see cref="ChatCompletionsClient"/>, <see cref="EmbeddingsClient"/>, <see cref="ImageEmbeddingsClient"/> to client builder. </summary>
+    /// <summary> Extension methods to add <see cref="ChatCompletionsClient"/> to client builder. </summary>
     public static partial class AIInferenceClientBuilderExtensions
     {
         /// <summary> Registers a <see cref="ChatCompletionsClient"/> instance. </summary>
         /// <param name="builder"> The builder to register with. </param>
         /// <param name="endpoint"> Service host. </param>
         /// <param name="credential"> A credential used to authenticate to an Azure Service. </param>
-        public static IAzureClientBuilder<ChatCompletionsClient, AzureAIInferenceClientOptions> AddChatCompletionsClient<TBuilder>(this TBuilder builder, Uri endpoint, AzureKeyCredential credential)
+        public static IAzureClientBuilder<ChatCompletionsClient, ChatCompletionsClientOptions> AddChatCompletionsClient<TBuilder>(this TBuilder builder, Uri endpoint, AzureKeyCredential credential)
         where TBuilder : IAzureClientFactoryBuilder
         {
-            return builder.RegisterClientFactory<ChatCompletionsClient, AzureAIInferenceClientOptions>((options) => new ChatCompletionsClient(endpoint, credential, options));
+            return builder.RegisterClientFactory<ChatCompletionsClient, ChatCompletionsClientOptions>((options) => new ChatCompletionsClient(endpoint, credential, options));
         }
 
         /// <summary> Registers a <see cref="ChatCompletionsClient"/> instance. </summary>
         /// <param name="builder"> The builder to register with. </param>
         /// <param name="endpoint"> Service host. </param>
-        public static IAzureClientBuilder<ChatCompletionsClient, AzureAIInferenceClientOptions> AddChatCompletionsClient<TBuilder>(this TBuilder builder, Uri endpoint)
+        public static IAzureClientBuilder<ChatCompletionsClient, ChatCompletionsClientOptions> AddChatCompletionsClient<TBuilder>(this TBuilder builder, Uri endpoint)
         where TBuilder : IAzureClientFactoryBuilderWithCredential
         {
-            return builder.RegisterClientFactory<ChatCompletionsClient, AzureAIInferenceClientOptions>((options, cred) => new ChatCompletionsClient(endpoint, cred, options));
-        }
-
-        /// <summary> Registers a <see cref="EmbeddingsClient"/> instance. </summary>
-        /// <param name="builder"> The builder to register with. </param>
-        /// <param name="endpoint"> Service host. </param>
-        /// <param name="credential"> A credential used to authenticate to an Azure Service. </param>
-        public static IAzureClientBuilder<EmbeddingsClient, AzureAIInferenceClientOptions> AddEmbeddingsClient<TBuilder>(this TBuilder builder, Uri endpoint, AzureKeyCredential credential)
-        where TBuilder : IAzureClientFactoryBuilder
-        {
-            return builder.RegisterClientFactory<EmbeddingsClient, AzureAIInferenceClientOptions>((options) => new EmbeddingsClient(endpoint, credential, options));
-        }
-
-        /// <summary> Registers a <see cref="EmbeddingsClient"/> instance. </summary>
-        /// <param name="builder"> The builder to register with. </param>
-        /// <param name="endpoint"> Service host. </param>
-        public static IAzureClientBuilder<EmbeddingsClient, AzureAIInferenceClientOptions> AddEmbeddingsClient<TBuilder>(this TBuilder builder, Uri endpoint)
-        where TBuilder : IAzureClientFactoryBuilderWithCredential
-        {
-            return builder.RegisterClientFactory<EmbeddingsClient, AzureAIInferenceClientOptions>((options, cred) => new EmbeddingsClient(endpoint, cred, options));
-        }
-
-        /// <summary> Registers a <see cref="ImageEmbeddingsClient"/> instance. </summary>
-        /// <param name="builder"> The builder to register with. </param>
-        /// <param name="endpoint"> Service host. </param>
-        /// <param name="credential"> A credential used to authenticate to an Azure Service. </param>
-        public static IAzureClientBuilder<ImageEmbeddingsClient, AzureAIInferenceClientOptions> AddImageEmbeddingsClient<TBuilder>(this TBuilder builder, Uri endpoint, AzureKeyCredential credential)
-        where TBuilder : IAzureClientFactoryBuilder
-        {
-            return builder.RegisterClientFactory<ImageEmbeddingsClient, AzureAIInferenceClientOptions>((options) => new ImageEmbeddingsClient(endpoint, credential, options));
-        }
-
-        /// <summary> Registers a <see cref="ImageEmbeddingsClient"/> instance. </summary>
-        /// <param name="builder"> The builder to register with. </param>
-        /// <param name="endpoint"> Service host. </param>
-        public static IAzureClientBuilder<ImageEmbeddingsClient, AzureAIInferenceClientOptions> AddImageEmbeddingsClient<TBuilder>(this TBuilder builder, Uri endpoint)
-        where TBuilder : IAzureClientFactoryBuilderWithCredential
-        {
-            return builder.RegisterClientFactory<ImageEmbeddingsClient, AzureAIInferenceClientOptions>((options, cred) => new ImageEmbeddingsClient(endpoint, cred, options));
+            return builder.RegisterClientFactory<ChatCompletionsClient, ChatCompletionsClientOptions>((options, cred) => new ChatCompletionsClient(endpoint, cred, options));
         }
 
         /// <summary> Registers a <see cref="ChatCompletionsClient"/> instance. </summary>
         /// <param name="builder"> The builder to register with. </param>
         /// <param name="configuration"> The configuration values. </param>
-        public static IAzureClientBuilder<ChatCompletionsClient, AzureAIInferenceClientOptions> AddChatCompletionsClient<TBuilder, TConfiguration>(this TBuilder builder, TConfiguration configuration)
-        where TBuilder : IAzureClientFactoryBuilderWithConfiguration<TConfiguration>
-        {
-            return builder.RegisterClientFactory<ChatCompletionsClient, AzureAIInferenceClientOptions>(configuration);
-        }
-        /// <summary> Registers a <see cref="EmbeddingsClient"/> instance. </summary>
-        /// <param name="builder"> The builder to register with. </param>
-        /// <param name="configuration"> The configuration values. </param>
-        public static IAzureClientBuilder<EmbeddingsClient, AzureAIInferenceClientOptions> AddEmbeddingsClient<TBuilder, TConfiguration>(this TBuilder builder, TConfiguration configuration)
-        where TBuilder : IAzureClientFactoryBuilderWithConfiguration<TConfiguration>
-        {
-            return builder.RegisterClientFactory<EmbeddingsClient, AzureAIInferenceClientOptions>(configuration);
-        }
-        /// <summary> Registers a <see cref="ImageEmbeddingsClient"/> instance. </summary>
-        /// <param name="builder"> The builder to register with. </param>
-        /// <param name="configuration"> The configuration values. </param>
-        public static IAzureClientBuilder<ImageEmbeddingsClient, AzureAIInferenceClientOptions> AddImageEmbeddingsClient<TBuilder, TConfiguration>(this TBuilder builder, TConfiguration configuration)
+        public static IAzureClientBuilder<ChatCompletionsClient, ChatCompletionsClientOptions> AddChatCompletionsClient<TBuilder, TConfiguration>(this TBuilder builder, TConfiguration configuration)
         where TBuilder : IAzureClientFactoryBuilderWithConfiguration<TConfiguration>
         {
-            return builder.RegisterClientFactory<ImageEmbeddingsClient, AzureAIInferenceClientOptions>(configuration);
+            return builder.RegisterClientFactory<ChatCompletionsClient, ChatCompletionsClientOptions>(configuration);
         }
     }
 }
diff --git a/sdk/ai/Azure.AI.Inference/src/Generated/AIInferenceModelFactory.cs b/sdk/ai/Azure.AI.Inference/src/Generated/AIInferenceModelFactory.cs
index 8bd673de3aa2..c2fde0770668 100644
--- a/sdk/ai/Azure.AI.Inference/src/Generated/AIInferenceModelFactory.cs
+++ b/sdk/ai/Azure.AI.Inference/src/Generated/AIInferenceModelFactory.cs
@@ -38,6 +38,22 @@ public static ChatMessageTextContentItem ChatMessageTextContentItem(string text
             return new ChatMessageTextContentItem("text", serializedAdditionalRawData: null, text);
         }
 
+        /// <summary> Initializes a new instance of <see cref="Inference.ChatMessageAudioUrlContentItem"/>. </summary>
+        /// <param name="audioUrl"> The details of the audio url. </param>
+        /// <returns> A new <see cref="Inference.ChatMessageAudioUrlContentItem"/> instance for mocking. </returns>
+        public static ChatMessageAudioUrlContentItem ChatMessageAudioUrlContentItem(ChatMessageInputAudioUrl audioUrl = null)
+        {
+            return new ChatMessageAudioUrlContentItem("audio_url", serializedAdditionalRawData: null, audioUrl);
+        }
+
+        /// <summary> Initializes a new instance of <see cref="Inference.ChatMessageAudioDataContentItem"/>. </summary>
+        /// <param name="inputAudio"> The details of the input audio data. </param>
+        /// <returns> A new <see cref="Inference.ChatMessageAudioDataContentItem"/> instance for mocking. </returns>
+        public static ChatMessageAudioDataContentItem ChatMessageAudioDataContentItem(ChatMessageInputAudio inputAudio = null)
+        {
+            return new ChatMessageAudioDataContentItem("input_audio", serializedAdditionalRawData: null, inputAudio);
+        }
+
         /// <summary> Initializes a new instance of <see cref="Inference.ChatCompletionsToolCall"/>. </summary>
         /// <param name="id"> The ID of the tool call. </param>
         /// <param name="type"> The type of tool call. Currently, only `function` is supported. </param>
@@ -57,6 +73,36 @@ public static ChatRequestToolMessage ChatRequestToolMessage(string content = nul
             return new ChatRequestToolMessage(ChatRole.Tool, serializedAdditionalRawData: null, content, toolCallId);
         }
 
+        /// <summary> Initializes a new instance of <see cref="Inference.ChatCompletionsResponseFormatJsonSchema"/>. </summary>
+        /// <param name="jsonSchema"> The definition of the required JSON schema in the response, and associated metadata. </param>
+        /// <returns> A new <see cref="Inference.ChatCompletionsResponseFormatJsonSchema"/> instance for mocking. </returns>
+        public static ChatCompletionsResponseFormatJsonSchema ChatCompletionsResponseFormatJsonSchema(ChatCompletionsResponseFormatJsonSchemaDefinition jsonSchema = null)
+        {
+            return new ChatCompletionsResponseFormatJsonSchema("json_schema", serializedAdditionalRawData: null, jsonSchema);
+        }
+
+        /// <summary> Initializes a new instance of <see cref="Inference.ChatCompletionsResponseFormatJsonSchemaDefinition"/>. </summary>
+        /// <param name="name"> A name that labels this JSON schema. Must be a-z, A-Z, 0-9, or contain underscores and dashes, with a maximum length of 64. </param>
+        /// <param name="schema">
+        /// The definition of the JSON schema. See https://json-schema.org/overview/what-is-jsonschema.
+        /// Note that AI models usually only support a subset of the keywords defined by JSON schema.
+        /// Consult your AI model documentation to determine what is supported.
+        /// </param>
+        /// <param name="description"> A description of the response format, used by the AI model to determine how to generate responses in this format. </param>
+        /// <param name="strict">
+        /// If set to true, the service will error out if the provided JSON schema contains keywords
+        /// not supported by the AI model. An example of such keyword may be `maxLength` for JSON type `string`.
+        /// If false, and the provided JSON schema contains keywords not supported by the AI model,
+        /// the AI model will not error out. Instead it will ignore the unsupported keywords.
+        /// </param>
+        /// <returns> A new <see cref="Inference.ChatCompletionsResponseFormatJsonSchemaDefinition"/> instance for mocking. </returns>
+        public static ChatCompletionsResponseFormatJsonSchemaDefinition ChatCompletionsResponseFormatJsonSchemaDefinition(string name = null, IDictionary<string, BinaryData> schema = null, string description = null, bool? strict = null)
+        {
+            schema ??= new Dictionary<string, BinaryData>();
+
+            return new ChatCompletionsResponseFormatJsonSchemaDefinition(name, schema, description, strict, serializedAdditionalRawData: null);
+        }
+
         /// <summary> Initializes a new instance of <see cref="Inference.ChatCompletionsToolDefinition"/>. </summary>
         /// <param name="type"> The type of the tool. Currently, only `function` is supported. </param>
         /// <param name="function"> The function definition details for the function tool. </param>
@@ -120,55 +166,6 @@ public static ModelInfo ModelInfo(string modelName = null, ModelType modelType =
             return new ModelInfo(modelName, modelType, modelProviderName, serializedAdditionalRawData: null);
         }
 
-        /// <summary> Initializes a new instance of <see cref="Inference.EmbeddingsResult"/>. </summary>
-        /// <param name="id"> Unique identifier for the embeddings result. </param>
-        /// <param name="data"> Embedding values for the prompts submitted in the request. </param>
-        /// <param name="usage"> Usage counts for tokens input using the embeddings API. </param>
-        /// <param name="model"> The model ID used to generate this result. </param>
-        /// <returns> A new <see cref="Inference.EmbeddingsResult"/> instance for mocking. </returns>
-        public static EmbeddingsResult EmbeddingsResult(string id = null, IEnumerable<EmbeddingItem> data = null, EmbeddingsUsage usage = null, string model = null)
-        {
-            data ??= new List<EmbeddingItem>();
-
-            return new EmbeddingsResult(id, data?.ToList(), usage, model, serializedAdditionalRawData: null);
-        }
-
-        /// <summary> Initializes a new instance of <see cref="Inference.EmbeddingItem"/>. </summary>
-        /// <param name="embedding">
-        /// List of embedding values for the input prompt. These represent a measurement of the
-        /// vector-based relatedness of the provided input. Or a base64 encoded string of the embedding vector.
-        /// </param>
-        /// <param name="index"> Index of the prompt to which the EmbeddingItem corresponds. </param>
-        /// <returns> A new <see cref="Inference.EmbeddingItem"/> instance for mocking. </returns>
-        public static EmbeddingItem EmbeddingItem(BinaryData embedding = null, int index = default)
-        {
-            return new EmbeddingItem(embedding, index, serializedAdditionalRawData: null);
-        }
-
-        /// <summary> Initializes a new instance of <see cref="Inference.EmbeddingsUsage"/>. </summary>
-        /// <param name="promptTokens"> Number of tokens in the request. </param>
-        /// <param name="totalTokens">
-        /// Total number of tokens transacted in this request/response. Should equal the
-        /// number of tokens in the request.
-        /// </param>
-        /// <returns> A new <see cref="Inference.EmbeddingsUsage"/> instance for mocking. </returns>
-        public static EmbeddingsUsage EmbeddingsUsage(int promptTokens = default, int totalTokens = default)
-        {
-            return new EmbeddingsUsage(promptTokens, totalTokens, serializedAdditionalRawData: null);
-        }
-
-        /// <summary> Initializes a new instance of <see cref="Inference.ImageEmbeddingInput"/>. </summary>
-        /// <param name="image"> The input image encoded in base64 string as a data URL. Example: `data:image/{format};base64,{data}`. </param>
-        /// <param name="text">
-        /// Optional. The text input to feed into the model (like DINO, CLIP).
-        /// Returns a 422 error if the model doesn't support the value or parameter.
-        /// </param>
-        /// <returns> A new <see cref="Inference.ImageEmbeddingInput"/> instance for mocking. </returns>
-        public static ImageEmbeddingInput ImageEmbeddingInput(string image = null, string text = null)
-        {
-            return new ImageEmbeddingInput(image, text, serializedAdditionalRawData: null);
-        }
-
         /// <summary> Initializes a new instance of <see cref="Inference.StreamingChatCompletionsUpdate"/>. </summary>
         /// <param name="id"> A unique identifier associated with this chat completions response. </param>
         /// <param name="created">
diff --git a/sdk/ai/Azure.AI.Inference/src/Generated/ChatCompletionsClient.cs b/sdk/ai/Azure.AI.Inference/src/Generated/ChatCompletionsClient.cs
index bc5b400f83fd..b485c9b5d334 100644
--- a/sdk/ai/Azure.AI.Inference/src/Generated/ChatCompletionsClient.cs
+++ b/sdk/ai/Azure.AI.Inference/src/Generated/ChatCompletionsClient.cs
@@ -6,8 +6,6 @@
 #nullable disable
 
 using System;
-using System.Collections.Generic;
-using System.Linq;
 using System.Threading;
 using System.Threading.Tasks;
 using Azure.Core;
@@ -43,7 +41,7 @@ protected ChatCompletionsClient()
         /// <param name="endpoint"> Service host. </param>
         /// <param name="credential"> A credential used to authenticate to an Azure Service. </param>
         /// <exception cref="ArgumentNullException"> <paramref name="endpoint"/> or <paramref name="credential"/> is null. </exception>
-        public ChatCompletionsClient(Uri endpoint, AzureKeyCredential credential) : this(endpoint, credential, new AzureAIInferenceClientOptions())
+        public ChatCompletionsClient(Uri endpoint, AzureKeyCredential credential) : this(endpoint, credential, new ChatCompletionsClientOptions())
         {
         }
 
@@ -51,7 +49,7 @@ protected ChatCompletionsClient()
         /// <param name="endpoint"> Service host. </param>
         /// <param name="credential"> A credential used to authenticate to an Azure Service. </param>
         /// <exception cref="ArgumentNullException"> <paramref name="endpoint"/> or <paramref name="credential"/> is null. </exception>
-        public ChatCompletionsClient(Uri endpoint, TokenCredential credential) : this(endpoint, credential, new AzureAIInferenceClientOptions())
+        public ChatCompletionsClient(Uri endpoint, TokenCredential credential) : this(endpoint, credential, new ChatCompletionsClientOptions())
         {
         }
 
@@ -60,11 +58,29 @@ protected ChatCompletionsClient()
         /// <param name="credential"> A credential used to authenticate to an Azure Service. </param>
         /// <param name="options"> The options for configuring the client. </param>
         /// <exception cref="ArgumentNullException"> <paramref name="endpoint"/> or <paramref name="credential"/> is null. </exception>
-        public ChatCompletionsClient(Uri endpoint, TokenCredential credential, AzureAIInferenceClientOptions options)
+        public ChatCompletionsClient(Uri endpoint, AzureKeyCredential credential, ChatCompletionsClientOptions options)
         {
             Argument.AssertNotNull(endpoint, nameof(endpoint));
             Argument.AssertNotNull(credential, nameof(credential));
-            options ??= new AzureAIInferenceClientOptions();
+            options ??= new ChatCompletionsClientOptions();
+
+            ClientDiagnostics = new ClientDiagnostics(options, true);
+            _keyCredential = credential;
+            _pipeline = HttpPipelineBuilder.Build(options, Array.Empty<HttpPipelinePolicy>(), new HttpPipelinePolicy[] { new AzureKeyCredentialPolicy(_keyCredential, AuthorizationHeader, AuthorizationApiKeyPrefix) }, new ResponseClassifier());
+            _endpoint = endpoint;
+            _apiVersion = options.Version;
+        }
+
+        /// <summary> Initializes a new instance of ChatCompletionsClient. </summary>
+        /// <param name="endpoint"> Service host. </param>
+        /// <param name="credential"> A credential used to authenticate to an Azure Service. </param>
+        /// <param name="options"> The options for configuring the client. </param>
+        /// <exception cref="ArgumentNullException"> <paramref name="endpoint"/> or <paramref name="credential"/> is null. </exception>
+        public ChatCompletionsClient(Uri endpoint, TokenCredential credential, ChatCompletionsClientOptions options)
+        {
+            Argument.AssertNotNull(endpoint, nameof(endpoint));
+            Argument.AssertNotNull(credential, nameof(credential));
+            options ??= new ChatCompletionsClientOptions();
 
             ClientDiagnostics = new ClientDiagnostics(options, true);
             _tokenCredential = credential;
@@ -73,6 +89,54 @@ public ChatCompletionsClient(Uri endpoint, TokenCredential credential, AzureAIIn
             _apiVersion = options.Version;
         }
 
+        /// <summary>
+        /// Gets chat completions for the provided chat messages.
+        /// Completions support a wide variety of tasks and generate text that continues from or "completes"
+        /// provided prompt data. The method makes a REST API call to the `/chat/completions` route
+        /// on the given endpoint.
+        /// </summary>
+        /// <param name="body"> The options for chat completions. </param>
+        /// <param name="extraParams">
+        /// Controls what happens if extra parameters, undefined by the REST API,
+        /// are passed in the JSON request payload.
+        /// This sets the HTTP request header `extra-parameters`.
+        /// </param>
+        /// <param name="cancellationToken"> The cancellation token to use. </param>
+        /// <exception cref="ArgumentNullException"> <paramref name="body"/> is null. </exception>
+        internal virtual async Task<Response<ChatCompletions>> CompleteAsync(ChatCompletionsOptions body, ExtraParameters? extraParams = null, CancellationToken cancellationToken = default)
+        {
+            Argument.AssertNotNull(body, nameof(body));
+
+            using RequestContent content = body.ToRequestContent();
+            RequestContext context = FromCancellationToken(cancellationToken);
+            Response response = await CompleteAsync(content, extraParams?.ToString(), context).ConfigureAwait(false);
+            return Response.FromValue(ChatCompletions.FromResponse(response), response);
+        }
+
+        /// <summary>
+        /// Gets chat completions for the provided chat messages.
+        /// Completions support a wide variety of tasks and generate text that continues from or "completes"
+        /// provided prompt data. The method makes a REST API call to the `/chat/completions` route
+        /// on the given endpoint.
+        /// </summary>
+        /// <param name="body"> The options for chat completions. </param>
+        /// <param name="extraParams">
+        /// Controls what happens if extra parameters, undefined by the REST API,
+        /// are passed in the JSON request payload.
+        /// This sets the HTTP request header `extra-parameters`.
+        /// </param>
+        /// <param name="cancellationToken"> The cancellation token to use. </param>
+        /// <exception cref="ArgumentNullException"> <paramref name="body"/> is null. </exception>
+        internal virtual Response<ChatCompletions> Complete(ChatCompletionsOptions body, ExtraParameters? extraParams = null, CancellationToken cancellationToken = default)
+        {
+            Argument.AssertNotNull(body, nameof(body));
+
+            using RequestContent content = body.ToRequestContent();
+            RequestContext context = FromCancellationToken(cancellationToken);
+            Response response = Complete(content, extraParams?.ToString(), context);
+            return Response.FromValue(ChatCompletions.FromResponse(response), response);
+        }
+
         /// <summary>
         /// Returns information about the AI model.
         /// The method makes a REST API call to the `/info` route on the given endpoint.
diff --git a/sdk/ai/Azure.AI.Inference/src/Generated/AzureAIInferenceClientOptions.cs b/sdk/ai/Azure.AI.Inference/src/Generated/ChatCompletionsClientOptions.cs
similarity index 70%
rename from sdk/ai/Azure.AI.Inference/src/Generated/AzureAIInferenceClientOptions.cs
rename to sdk/ai/Azure.AI.Inference/src/Generated/ChatCompletionsClientOptions.cs
index 46dcb4716cad..e68f1c4ec7fb 100644
--- a/sdk/ai/Azure.AI.Inference/src/Generated/AzureAIInferenceClientOptions.cs
+++ b/sdk/ai/Azure.AI.Inference/src/Generated/ChatCompletionsClientOptions.cs
@@ -10,8 +10,8 @@
 
 namespace Azure.AI.Inference
 {
-    /// <summary> Client options for Azure.AI.Inference library clients. </summary>
-    public partial class AzureAIInferenceClientOptions : ClientOptions
+    /// <summary> Client options for ChatCompletionsClient. </summary>
+    public partial class ChatCompletionsClientOptions : ClientOptions
     {
         private const ServiceVersion LatestVersion = ServiceVersion.V2024_05_01_Preview;
 
@@ -24,8 +24,8 @@ public enum ServiceVersion
 
         internal string Version { get; }
 
-        /// <summary> Initializes new instance of AzureAIInferenceClientOptions. </summary>
-        public AzureAIInferenceClientOptions(ServiceVersion version = LatestVersion)
+        /// <summary> Initializes new instance of ChatCompletionsClientOptions. </summary>
+        public ChatCompletionsClientOptions(ServiceVersion version = LatestVersion)
         {
             Version = version switch
             {
diff --git a/sdk/ai/Azure.AI.Inference/src/Generated/ChatCompletionsOptions.cs b/sdk/ai/Azure.AI.Inference/src/Generated/ChatCompletionsOptions.cs
index 7bcda3441011..49b76cdab0f9 100644
--- a/sdk/ai/Azure.AI.Inference/src/Generated/ChatCompletionsOptions.cs
+++ b/sdk/ai/Azure.AI.Inference/src/Generated/ChatCompletionsOptions.cs
@@ -89,7 +89,7 @@ public ChatCompletionsOptions(IEnumerable<ChatRequestMessage> messages)
         ///
         /// **Important:** when using JSON mode, you **must** also instruct the model to produce JSON yourself via a system or user message. Without this, the model may generate an unending stream of whitespace until the generation reaches the token limit, resulting in a long-running and seemingly "stuck" request. Also note that the message content may be partially cut off if `finish_reason="length"`, which indicates the generation exceeded `max_tokens` or the conversation exceeded the max context length.
         /// Please note <see cref="ChatCompletionsResponseFormat"/> is the base class. According to the scenario, a derived class of the base class might need to be assigned here, or this property needs to be casted to one of the possible derived classes.
-        /// The available derived classes include <see cref="ChatCompletionsResponseFormatJsonObject"/> and <see cref="ChatCompletionsResponseFormatText"/>.
+        /// The available derived classes include <see cref="ChatCompletionsResponseFormatJsonObject"/>, <see cref="ChatCompletionsResponseFormatJsonSchema"/> and <see cref="ChatCompletionsResponseFormatText"/>.
         /// </param>
         /// <param name="stopSequences"> A collection of textual sequences that will end completions generation. </param>
         /// <param name="tools">
@@ -166,7 +166,7 @@ internal ChatCompletionsOptions(IList<ChatRequestMessage> messages, float? frequ
         ///
         /// **Important:** when using JSON mode, you **must** also instruct the model to produce JSON yourself via a system or user message. Without this, the model may generate an unending stream of whitespace until the generation reaches the token limit, resulting in a long-running and seemingly "stuck" request. Also note that the message content may be partially cut off if `finish_reason="length"`, which indicates the generation exceeded `max_tokens` or the conversation exceeded the max context length.
         /// Please note <see cref="ChatCompletionsResponseFormat"/> is the base class. According to the scenario, a derived class of the base class might need to be assigned here, or this property needs to be casted to one of the possible derived classes.
-        /// The available derived classes include <see cref="ChatCompletionsResponseFormatJsonObject"/> and <see cref="ChatCompletionsResponseFormatText"/>.
+        /// The available derived classes include <see cref="ChatCompletionsResponseFormatJsonObject"/>, <see cref="ChatCompletionsResponseFormatJsonSchema"/> and <see cref="ChatCompletionsResponseFormatText"/>.
         /// </summary>
         public ChatCompletionsResponseFormat ResponseFormat { get; set; }
         /// <summary> A collection of textual sequences that will end completions generation. </summary>
diff --git a/sdk/ai/Azure.AI.Inference/src/Generated/ChatCompletionsResponseFormat.cs b/sdk/ai/Azure.AI.Inference/src/Generated/ChatCompletionsResponseFormat.cs
index 0bb1aeceeb2a..4c0e48732ac6 100644
--- a/sdk/ai/Azure.AI.Inference/src/Generated/ChatCompletionsResponseFormat.cs
+++ b/sdk/ai/Azure.AI.Inference/src/Generated/ChatCompletionsResponseFormat.cs
@@ -15,7 +15,7 @@ namespace Azure.AI.Inference
     /// Note that to enable JSON mode, some AI models may also require you to instruct the model to produce JSON
     /// via a system or user message.
     /// Please note <see cref="ChatCompletionsResponseFormat"/> is the base class. According to the scenario, a derived class of the base class might need to be assigned here, or this property needs to be casted to one of the possible derived classes.
-    /// The available derived classes include <see cref="ChatCompletionsResponseFormatJsonObject"/> and <see cref="ChatCompletionsResponseFormatText"/>.
+    /// The available derived classes include <see cref="ChatCompletionsResponseFormatJsonObject"/>, <see cref="ChatCompletionsResponseFormatJsonSchema"/> and <see cref="ChatCompletionsResponseFormatText"/>.
     /// </summary>
     public abstract partial class ChatCompletionsResponseFormat
     {
diff --git a/sdk/ai/Azure.AI.Inference/src/Generated/ChatCompletionsResponseFormatJsonSchema.Serialization.cs b/sdk/ai/Azure.AI.Inference/src/Generated/ChatCompletionsResponseFormatJsonSchema.Serialization.cs
index 27b9d9c6e41e..583f02f1bc1c 100644
--- a/sdk/ai/Azure.AI.Inference/src/Generated/ChatCompletionsResponseFormatJsonSchema.Serialization.cs
+++ b/sdk/ai/Azure.AI.Inference/src/Generated/ChatCompletionsResponseFormatJsonSchema.Serialization.cs
@@ -13,7 +13,7 @@
 
 namespace Azure.AI.Inference
 {
-    internal partial class ChatCompletionsResponseFormatJsonSchema : IUtf8JsonSerializable, IJsonModel<ChatCompletionsResponseFormatJsonSchema>
+    public partial class ChatCompletionsResponseFormatJsonSchema : IUtf8JsonSerializable, IJsonModel<ChatCompletionsResponseFormatJsonSchema>
     {
         void IUtf8JsonSerializable.Write(Utf8JsonWriter writer) => ((IJsonModel<ChatCompletionsResponseFormatJsonSchema>)this).Write(writer, ModelSerializationExtensions.WireOptions);
 
diff --git a/sdk/ai/Azure.AI.Inference/src/Generated/ChatCompletionsResponseFormatJsonSchema.cs b/sdk/ai/Azure.AI.Inference/src/Generated/ChatCompletionsResponseFormatJsonSchema.cs
index f6932d2b4955..58f1ede0d3b0 100644
--- a/sdk/ai/Azure.AI.Inference/src/Generated/ChatCompletionsResponseFormatJsonSchema.cs
+++ b/sdk/ai/Azure.AI.Inference/src/Generated/ChatCompletionsResponseFormatJsonSchema.cs
@@ -14,7 +14,7 @@ namespace Azure.AI.Inference
     /// A response format for Chat Completions that restricts responses to emitting valid JSON objects, with a
     /// JSON schema specified by the caller.
     /// </summary>
-    internal partial class ChatCompletionsResponseFormatJsonSchema : ChatCompletionsResponseFormat
+    public partial class ChatCompletionsResponseFormatJsonSchema : ChatCompletionsResponseFormat
     {
         /// <summary> Initializes a new instance of <see cref="ChatCompletionsResponseFormatJsonSchema"/>. </summary>
         /// <param name="jsonSchema"> The definition of the required JSON schema in the response, and associated metadata. </param>
diff --git a/sdk/ai/Azure.AI.Inference/src/Generated/ChatCompletionsResponseFormatJsonSchemaDefinition.Serialization.cs b/sdk/ai/Azure.AI.Inference/src/Generated/ChatCompletionsResponseFormatJsonSchemaDefinition.Serialization.cs
index 293b368904eb..e2ef56fe85e7 100644
--- a/sdk/ai/Azure.AI.Inference/src/Generated/ChatCompletionsResponseFormatJsonSchemaDefinition.Serialization.cs
+++ b/sdk/ai/Azure.AI.Inference/src/Generated/ChatCompletionsResponseFormatJsonSchemaDefinition.Serialization.cs
@@ -13,7 +13,7 @@
 
 namespace Azure.AI.Inference
 {
-    internal partial class ChatCompletionsResponseFormatJsonSchemaDefinition : IUtf8JsonSerializable, IJsonModel<ChatCompletionsResponseFormatJsonSchemaDefinition>
+    public partial class ChatCompletionsResponseFormatJsonSchemaDefinition : IUtf8JsonSerializable, IJsonModel<ChatCompletionsResponseFormatJsonSchemaDefinition>
     {
         void IUtf8JsonSerializable.Write(Utf8JsonWriter writer) => ((IJsonModel<ChatCompletionsResponseFormatJsonSchemaDefinition>)this).Write(writer, ModelSerializationExtensions.WireOptions);
 
diff --git a/sdk/ai/Azure.AI.Inference/src/Generated/ChatCompletionsResponseFormatJsonSchemaDefinition.cs b/sdk/ai/Azure.AI.Inference/src/Generated/ChatCompletionsResponseFormatJsonSchemaDefinition.cs
index 749179704791..2f57877b44ae 100644
--- a/sdk/ai/Azure.AI.Inference/src/Generated/ChatCompletionsResponseFormatJsonSchemaDefinition.cs
+++ b/sdk/ai/Azure.AI.Inference/src/Generated/ChatCompletionsResponseFormatJsonSchemaDefinition.cs
@@ -14,7 +14,7 @@ namespace Azure.AI.Inference
     /// Defines the response format for chat completions as JSON with a given schema.
     /// The AI model will need to adhere to this schema when generating completions.
     /// </summary>
-    internal partial class ChatCompletionsResponseFormatJsonSchemaDefinition
+    public partial class ChatCompletionsResponseFormatJsonSchemaDefinition
     {
         /// <summary>
         /// Keeps track of any properties unknown to the library.
diff --git a/sdk/ai/Azure.AI.Inference/src/Generated/ChatMessageAudioDataContentItem.Serialization.cs b/sdk/ai/Azure.AI.Inference/src/Generated/ChatMessageAudioDataContentItem.Serialization.cs
index 22cef9b1ea34..ea763c25ae97 100644
--- a/sdk/ai/Azure.AI.Inference/src/Generated/ChatMessageAudioDataContentItem.Serialization.cs
+++ b/sdk/ai/Azure.AI.Inference/src/Generated/ChatMessageAudioDataContentItem.Serialization.cs
@@ -13,7 +13,7 @@
 
 namespace Azure.AI.Inference
 {
-    internal partial class ChatMessageAudioDataContentItem : IUtf8JsonSerializable, IJsonModel<ChatMessageAudioDataContentItem>
+    public partial class ChatMessageAudioDataContentItem : IUtf8JsonSerializable, IJsonModel<ChatMessageAudioDataContentItem>
     {
         void IUtf8JsonSerializable.Write(Utf8JsonWriter writer) => ((IJsonModel<ChatMessageAudioDataContentItem>)this).Write(writer, ModelSerializationExtensions.WireOptions);
 
diff --git a/sdk/ai/Azure.AI.Inference/src/Generated/ChatMessageAudioDataContentItem.cs b/sdk/ai/Azure.AI.Inference/src/Generated/ChatMessageAudioDataContentItem.cs
index 28f939ee09a9..de8ead7ebcce 100644
--- a/sdk/ai/Azure.AI.Inference/src/Generated/ChatMessageAudioDataContentItem.cs
+++ b/sdk/ai/Azure.AI.Inference/src/Generated/ChatMessageAudioDataContentItem.cs
@@ -11,7 +11,7 @@
 namespace Azure.AI.Inference
 {
     /// <summary> A structured chat content item for audio content passed as base64 encoded data. </summary>
-    internal partial class ChatMessageAudioDataContentItem : ChatMessageContentItem
+    public partial class ChatMessageAudioDataContentItem : ChatMessageContentItem
     {
         /// <summary> Initializes a new instance of <see cref="ChatMessageAudioDataContentItem"/>. </summary>
         /// <param name="inputAudio"> The details of the input audio data. </param>
diff --git a/sdk/ai/Azure.AI.Inference/src/Generated/ChatMessageAudioUrlContentItem.Serialization.cs b/sdk/ai/Azure.AI.Inference/src/Generated/ChatMessageAudioUrlContentItem.Serialization.cs
index 62f4b2fe15ca..64c0debaa2e6 100644
--- a/sdk/ai/Azure.AI.Inference/src/Generated/ChatMessageAudioUrlContentItem.Serialization.cs
+++ b/sdk/ai/Azure.AI.Inference/src/Generated/ChatMessageAudioUrlContentItem.Serialization.cs
@@ -13,7 +13,7 @@
 
 namespace Azure.AI.Inference
 {
-    internal partial class ChatMessageAudioUrlContentItem : IUtf8JsonSerializable, IJsonModel<ChatMessageAudioUrlContentItem>
+    public partial class ChatMessageAudioUrlContentItem : IUtf8JsonSerializable, IJsonModel<ChatMessageAudioUrlContentItem>
     {
         void IUtf8JsonSerializable.Write(Utf8JsonWriter writer) => ((IJsonModel<ChatMessageAudioUrlContentItem>)this).Write(writer, ModelSerializationExtensions.WireOptions);
 
diff --git a/sdk/ai/Azure.AI.Inference/src/Generated/ChatMessageAudioUrlContentItem.cs b/sdk/ai/Azure.AI.Inference/src/Generated/ChatMessageAudioUrlContentItem.cs
index 36aa6cad1fe0..27b2c755180b 100644
--- a/sdk/ai/Azure.AI.Inference/src/Generated/ChatMessageAudioUrlContentItem.cs
+++ b/sdk/ai/Azure.AI.Inference/src/Generated/ChatMessageAudioUrlContentItem.cs
@@ -11,7 +11,7 @@
 namespace Azure.AI.Inference
 {
     /// <summary> A structured chat content item for audio content passed as a url. </summary>
-    internal partial class ChatMessageAudioUrlContentItem : ChatMessageContentItem
+    public partial class ChatMessageAudioUrlContentItem : ChatMessageContentItem
     {
         /// <summary> Initializes a new instance of <see cref="ChatMessageAudioUrlContentItem"/>. </summary>
         /// <param name="audioUrl"> The details of the audio url. </param>
diff --git a/sdk/ai/Azure.AI.Inference/src/Generated/ChatMessageContentItem.cs b/sdk/ai/Azure.AI.Inference/src/Generated/ChatMessageContentItem.cs
index 3c1131052b9b..005c8f3090b9 100644
--- a/sdk/ai/Azure.AI.Inference/src/Generated/ChatMessageContentItem.cs
+++ b/sdk/ai/Azure.AI.Inference/src/Generated/ChatMessageContentItem.cs
@@ -13,7 +13,7 @@ namespace Azure.AI.Inference
     /// <summary>
     /// An abstract representation of a structured content item within a chat message.
     /// Please note <see cref="ChatMessageContentItem"/> is the base class. According to the scenario, a derived class of the base class might need to be assigned here, or this property needs to be casted to one of the possible derived classes.
-    /// The available derived classes include <see cref="ChatMessageImageContentItem"/> and <see cref="ChatMessageTextContentItem"/>.
+    /// The available derived classes include <see cref="ChatMessageAudioUrlContentItem"/>, <see cref="ChatMessageImageContentItem"/>, <see cref="ChatMessageAudioDataContentItem"/> and <see cref="ChatMessageTextContentItem"/>.
     /// </summary>
     public abstract partial class ChatMessageContentItem
     {
diff --git a/sdk/ai/Azure.AI.Inference/src/Generated/ChatMessageInputAudioUrl.Serialization.cs b/sdk/ai/Azure.AI.Inference/src/Generated/ChatMessageInputAudioUrl.Serialization.cs
index d644daee2e96..0552bd96a5d9 100644
--- a/sdk/ai/Azure.AI.Inference/src/Generated/ChatMessageInputAudioUrl.Serialization.cs
+++ b/sdk/ai/Azure.AI.Inference/src/Generated/ChatMessageInputAudioUrl.Serialization.cs
@@ -13,7 +13,7 @@
 
 namespace Azure.AI.Inference
 {
-    internal partial class ChatMessageInputAudioUrl : IUtf8JsonSerializable, IJsonModel<ChatMessageInputAudioUrl>
+    public partial class ChatMessageInputAudioUrl : IUtf8JsonSerializable, IJsonModel<ChatMessageInputAudioUrl>
     {
         void IUtf8JsonSerializable.Write(Utf8JsonWriter writer) => ((IJsonModel<ChatMessageInputAudioUrl>)this).Write(writer, ModelSerializationExtensions.WireOptions);
 
diff --git a/sdk/ai/Azure.AI.Inference/src/Generated/ChatMessageInputAudioUrl.cs b/sdk/ai/Azure.AI.Inference/src/Generated/ChatMessageInputAudioUrl.cs
index 3d10e3b2eede..df89ba820d20 100644
--- a/sdk/ai/Azure.AI.Inference/src/Generated/ChatMessageInputAudioUrl.cs
+++ b/sdk/ai/Azure.AI.Inference/src/Generated/ChatMessageInputAudioUrl.cs
@@ -11,7 +11,7 @@
 namespace Azure.AI.Inference
 {
     /// <summary> The details of the audio url. </summary>
-    internal partial class ChatMessageInputAudioUrl
+    public partial class ChatMessageInputAudioUrl
     {
         /// <summary>
         /// Keeps track of any properties unknown to the library.
diff --git a/sdk/ai/Azure.AI.Inference/src/Generated/CompleteRequest.Serialization.cs b/sdk/ai/Azure.AI.Inference/src/Generated/CompleteRequest.Serialization.cs
deleted file mode 100644
index 5f529fd16cd5..000000000000
--- a/sdk/ai/Azure.AI.Inference/src/Generated/CompleteRequest.Serialization.cs
+++ /dev/null
@@ -1,363 +0,0 @@
-// Copyright (c) Microsoft Corporation. All rights reserved.
-// Licensed under the MIT License.
-
-// <auto-generated/>
-
-#nullable disable
-
-using System;
-using System.ClientModel.Primitives;
-using System.Collections.Generic;
-using System.Text.Json;
-using Azure.Core;
-
-namespace Azure.AI.Inference
-{
-    internal partial class CompleteRequest : IUtf8JsonSerializable, IJsonModel<CompleteRequest>
-    {
-        void IUtf8JsonSerializable.Write(Utf8JsonWriter writer) => ((IJsonModel<CompleteRequest>)this).Write(writer, ModelSerializationExtensions.WireOptions);
-
-        void IJsonModel<CompleteRequest>.Write(Utf8JsonWriter writer, ModelReaderWriterOptions options)
-        {
-            writer.WriteStartObject();
-            JsonModelWriteCore(writer, options);
-            writer.WriteEndObject();
-        }
-
-        /// <param name="writer"> The JSON writer. </param>
-        /// <param name="options"> The client options for reading and writing models. </param>
-        protected virtual void JsonModelWriteCore(Utf8JsonWriter writer, ModelReaderWriterOptions options)
-        {
-            var format = options.Format == "W" ? ((IPersistableModel<CompleteRequest>)this).GetFormatFromOptions(options) : options.Format;
-            if (format != "J")
-            {
-                throw new FormatException($"The model {nameof(CompleteRequest)} does not support writing '{format}' format.");
-            }
-
-            writer.WritePropertyName("messages"u8);
-            writer.WriteStartArray();
-            foreach (var item in Messages)
-            {
-                writer.WriteObjectValue(item, options);
-            }
-            writer.WriteEndArray();
-            if (Optional.IsDefined(FrequencyPenalty))
-            {
-                writer.WritePropertyName("frequency_penalty"u8);
-                writer.WriteNumberValue(FrequencyPenalty.Value);
-            }
-            if (Optional.IsDefined(InternalShouldStreamResponse))
-            {
-                writer.WritePropertyName("stream"u8);
-                writer.WriteBooleanValue(InternalShouldStreamResponse.Value);
-            }
-            if (Optional.IsDefined(PresencePenalty))
-            {
-                writer.WritePropertyName("presence_penalty"u8);
-                writer.WriteNumberValue(PresencePenalty.Value);
-            }
-            if (Optional.IsDefined(Temperature))
-            {
-                writer.WritePropertyName("temperature"u8);
-                writer.WriteNumberValue(Temperature.Value);
-            }
-            if (Optional.IsDefined(NucleusSamplingFactor))
-            {
-                writer.WritePropertyName("top_p"u8);
-                writer.WriteNumberValue(NucleusSamplingFactor.Value);
-            }
-            if (Optional.IsDefined(MaxTokens))
-            {
-                writer.WritePropertyName("max_tokens"u8);
-                writer.WriteNumberValue(MaxTokens.Value);
-            }
-            if (Optional.IsDefined(ResponseFormat))
-            {
-                writer.WritePropertyName("response_format"u8);
-                writer.WriteObjectValue(ResponseFormat, options);
-            }
-            if (Optional.IsCollectionDefined(StopSequences))
-            {
-                writer.WritePropertyName("stop"u8);
-                writer.WriteStartArray();
-                foreach (var item in StopSequences)
-                {
-                    writer.WriteStringValue(item);
-                }
-                writer.WriteEndArray();
-            }
-            if (Optional.IsCollectionDefined(Tools))
-            {
-                writer.WritePropertyName("tools"u8);
-                writer.WriteStartArray();
-                foreach (var item in Tools)
-                {
-                    writer.WriteObjectValue(item, options);
-                }
-                writer.WriteEndArray();
-            }
-            if (Optional.IsDefined(ToolChoice))
-            {
-                writer.WritePropertyName("tool_choice"u8);
-#if NET6_0_OR_GREATER
-				writer.WriteRawValue(ToolChoice);
-#else
-                using (JsonDocument document = JsonDocument.Parse(ToolChoice, ModelSerializationExtensions.JsonDocumentOptions))
-                {
-                    JsonSerializer.Serialize(writer, document.RootElement);
-                }
-#endif
-            }
-            if (Optional.IsDefined(Seed))
-            {
-                writer.WritePropertyName("seed"u8);
-                writer.WriteNumberValue(Seed.Value);
-            }
-            if (Optional.IsDefined(Model))
-            {
-                writer.WritePropertyName("model"u8);
-                writer.WriteStringValue(Model);
-            }
-            foreach (var item in AdditionalProperties)
-            {
-                writer.WritePropertyName(item.Key);
-#if NET6_0_OR_GREATER
-				writer.WriteRawValue(item.Value);
-#else
-                using (JsonDocument document = JsonDocument.Parse(item.Value, ModelSerializationExtensions.JsonDocumentOptions))
-                {
-                    JsonSerializer.Serialize(writer, document.RootElement);
-                }
-#endif
-            }
-        }
-
-        CompleteRequest IJsonModel<CompleteRequest>.Create(ref Utf8JsonReader reader, ModelReaderWriterOptions options)
-        {
-            var format = options.Format == "W" ? ((IPersistableModel<CompleteRequest>)this).GetFormatFromOptions(options) : options.Format;
-            if (format != "J")
-            {
-                throw new FormatException($"The model {nameof(CompleteRequest)} does not support reading '{format}' format.");
-            }
-
-            using JsonDocument document = JsonDocument.ParseValue(ref reader);
-            return DeserializeCompleteRequest(document.RootElement, options);
-        }
-
-        internal static CompleteRequest DeserializeCompleteRequest(JsonElement element, ModelReaderWriterOptions options = null)
-        {
-            options ??= ModelSerializationExtensions.WireOptions;
-
-            if (element.ValueKind == JsonValueKind.Null)
-            {
-                return null;
-            }
-            IReadOnlyList<ChatRequestMessage> messages = default;
-            float? frequencyPenalty = default;
-            bool? stream = default;
-            float? presencePenalty = default;
-            float? temperature = default;
-            float? topP = default;
-            int? maxTokens = default;
-            ChatCompletionsResponseFormat responseFormat = default;
-            IReadOnlyList<string> stop = default;
-            IReadOnlyList<ChatCompletionsToolDefinition> tools = default;
-            BinaryData toolChoice = default;
-            long? seed = default;
-            string model = default;
-            IReadOnlyDictionary<string, BinaryData> additionalProperties = default;
-            Dictionary<string, BinaryData> additionalPropertiesDictionary = new Dictionary<string, BinaryData>();
-            foreach (var property in element.EnumerateObject())
-            {
-                if (property.NameEquals("messages"u8))
-                {
-                    List<ChatRequestMessage> array = new List<ChatRequestMessage>();
-                    foreach (var item in property.Value.EnumerateArray())
-                    {
-                        array.Add(ChatRequestMessage.DeserializeChatRequestMessage(item, options));
-                    }
-                    messages = array;
-                    continue;
-                }
-                if (property.NameEquals("frequency_penalty"u8))
-                {
-                    if (property.Value.ValueKind == JsonValueKind.Null)
-                    {
-                        continue;
-                    }
-                    frequencyPenalty = property.Value.GetSingle();
-                    continue;
-                }
-                if (property.NameEquals("stream"u8))
-                {
-                    if (property.Value.ValueKind == JsonValueKind.Null)
-                    {
-                        continue;
-                    }
-                    stream = property.Value.GetBoolean();
-                    continue;
-                }
-                if (property.NameEquals("presence_penalty"u8))
-                {
-                    if (property.Value.ValueKind == JsonValueKind.Null)
-                    {
-                        continue;
-                    }
-                    presencePenalty = property.Value.GetSingle();
-                    continue;
-                }
-                if (property.NameEquals("temperature"u8))
-                {
-                    if (property.Value.ValueKind == JsonValueKind.Null)
-                    {
-                        continue;
-                    }
-                    temperature = property.Value.GetSingle();
-                    continue;
-                }
-                if (property.NameEquals("top_p"u8))
-                {
-                    if (property.Value.ValueKind == JsonValueKind.Null)
-                    {
-                        continue;
-                    }
-                    topP = property.Value.GetSingle();
-                    continue;
-                }
-                if (property.NameEquals("max_tokens"u8))
-                {
-                    if (property.Value.ValueKind == JsonValueKind.Null)
-                    {
-                        continue;
-                    }
-                    maxTokens = property.Value.GetInt32();
-                    continue;
-                }
-                if (property.NameEquals("response_format"u8))
-                {
-                    if (property.Value.ValueKind == JsonValueKind.Null)
-                    {
-                        continue;
-                    }
-                    responseFormat = ChatCompletionsResponseFormat.DeserializeChatCompletionsResponseFormat(property.Value, options);
-                    continue;
-                }
-                if (property.NameEquals("stop"u8))
-                {
-                    if (property.Value.ValueKind == JsonValueKind.Null)
-                    {
-                        continue;
-                    }
-                    List<string> array = new List<string>();
-                    foreach (var item in property.Value.EnumerateArray())
-                    {
-                        array.Add(item.GetString());
-                    }
-                    stop = array;
-                    continue;
-                }
-                if (property.NameEquals("tools"u8))
-                {
-                    if (property.Value.ValueKind == JsonValueKind.Null)
-                    {
-                        continue;
-                    }
-                    List<ChatCompletionsToolDefinition> array = new List<ChatCompletionsToolDefinition>();
-                    foreach (var item in property.Value.EnumerateArray())
-                    {
-                        array.Add(ChatCompletionsToolDefinition.DeserializeChatCompletionsToolDefinition(item, options));
-                    }
-                    tools = array;
-                    continue;
-                }
-                if (property.NameEquals("tool_choice"u8))
-                {
-                    if (property.Value.ValueKind == JsonValueKind.Null)
-                    {
-                        continue;
-                    }
-                    toolChoice = BinaryData.FromString(property.Value.GetRawText());
-                    continue;
-                }
-                if (property.NameEquals("seed"u8))
-                {
-                    if (property.Value.ValueKind == JsonValueKind.Null)
-                    {
-                        continue;
-                    }
-                    seed = property.Value.GetInt64();
-                    continue;
-                }
-                if (property.NameEquals("model"u8))
-                {
-                    model = property.Value.GetString();
-                    continue;
-                }
-                additionalPropertiesDictionary.Add(property.Name, BinaryData.FromString(property.Value.GetRawText()));
-            }
-            additionalProperties = additionalPropertiesDictionary;
-            return new CompleteRequest(
-                messages,
-                frequencyPenalty,
-                stream,
-                presencePenalty,
-                temperature,
-                topP,
-                maxTokens,
-                responseFormat,
-                stop ?? new ChangeTrackingList<string>(),
-                tools ?? new ChangeTrackingList<ChatCompletionsToolDefinition>(),
-                toolChoice,
-                seed,
-                model,
-                additionalProperties);
-        }
-
-        BinaryData IPersistableModel<CompleteRequest>.Write(ModelReaderWriterOptions options)
-        {
-            var format = options.Format == "W" ? ((IPersistableModel<CompleteRequest>)this).GetFormatFromOptions(options) : options.Format;
-
-            switch (format)
-            {
-                case "J":
-                    return ModelReaderWriter.Write(this, options);
-                default:
-                    throw new FormatException($"The model {nameof(CompleteRequest)} does not support writing '{options.Format}' format.");
-            }
-        }
-
-        CompleteRequest IPersistableModel<CompleteRequest>.Create(BinaryData data, ModelReaderWriterOptions options)
-        {
-            var format = options.Format == "W" ? ((IPersistableModel<CompleteRequest>)this).GetFormatFromOptions(options) : options.Format;
-
-            switch (format)
-            {
-                case "J":
-                    {
-                        using JsonDocument document = JsonDocument.Parse(data, ModelSerializationExtensions.JsonDocumentOptions);
-                        return DeserializeCompleteRequest(document.RootElement, options);
-                    }
-                default:
-                    throw new FormatException($"The model {nameof(CompleteRequest)} does not support reading '{options.Format}' format.");
-            }
-        }
-
-        string IPersistableModel<CompleteRequest>.GetFormatFromOptions(ModelReaderWriterOptions options) => "J";
-
-        /// <summary> Deserializes the model from a raw response. </summary>
-        /// <param name="response"> The response to deserialize the model from. </param>
-        internal static CompleteRequest FromResponse(Response response)
-        {
-            using var document = JsonDocument.Parse(response.Content, ModelSerializationExtensions.JsonDocumentOptions);
-            return DeserializeCompleteRequest(document.RootElement);
-        }
-
-        /// <summary> Convert into a <see cref="RequestContent"/>. </summary>
-        internal virtual RequestContent ToRequestContent()
-        {
-            var content = new Utf8JsonRequestContent();
-            content.JsonWriter.WriteObjectValue(this, ModelSerializationExtensions.WireOptions);
-            return content;
-        }
-    }
-}
diff --git a/sdk/ai/Azure.AI.Inference/src/Generated/CompleteRequest.cs b/sdk/ai/Azure.AI.Inference/src/Generated/CompleteRequest.cs
deleted file mode 100644
index 596d83bd87d4..000000000000
--- a/sdk/ai/Azure.AI.Inference/src/Generated/CompleteRequest.cs
+++ /dev/null
@@ -1,273 +0,0 @@
-// Copyright (c) Microsoft Corporation. All rights reserved.
-// Licensed under the MIT License.
-
-// <auto-generated/>
-
-#nullable disable
-
-using System;
-using System.Collections.Generic;
-using System.Linq;
-
-namespace Azure.AI.Inference
-{
-    /// <summary> The CompleteRequest. </summary>
-    internal partial class CompleteRequest
-    {
-        /// <summary> Initializes a new instance of <see cref="CompleteRequest"/>. </summary>
-        /// <param name="messages">
-        /// The collection of context messages associated with this chat completions request.
-        /// Typical usage begins with a chat message for the System role that provides instructions for
-        /// the behavior of the assistant, followed by alternating messages between the User and
-        /// Assistant roles.
-        /// Please note <see cref="ChatRequestMessage"/> is the base class. According to the scenario, a derived class of the base class might need to be assigned here, or this property needs to be casted to one of the possible derived classes.
-        /// The available derived classes include <see cref="ChatRequestAssistantMessage"/>, <see cref="ChatRequestDeveloperMessage"/>, <see cref="ChatRequestSystemMessage"/>, <see cref="ChatRequestToolMessage"/> and <see cref="ChatRequestUserMessage"/>.
-        /// </param>
-        /// <exception cref="ArgumentNullException"> <paramref name="messages"/> is null. </exception>
-        internal CompleteRequest(IEnumerable<ChatRequestMessage> messages)
-        {
-            Argument.AssertNotNull(messages, nameof(messages));
-
-            Messages = messages.ToList();
-            StopSequences = new ChangeTrackingList<string>();
-            Tools = new ChangeTrackingList<ChatCompletionsToolDefinition>();
-            AdditionalProperties = new ChangeTrackingDictionary<string, BinaryData>();
-        }
-
-        /// <summary> Initializes a new instance of <see cref="CompleteRequest"/>. </summary>
-        /// <param name="messages">
-        /// The collection of context messages associated with this chat completions request.
-        /// Typical usage begins with a chat message for the System role that provides instructions for
-        /// the behavior of the assistant, followed by alternating messages between the User and
-        /// Assistant roles.
-        /// Please note <see cref="ChatRequestMessage"/> is the base class. According to the scenario, a derived class of the base class might need to be assigned here, or this property needs to be casted to one of the possible derived classes.
-        /// The available derived classes include <see cref="ChatRequestAssistantMessage"/>, <see cref="ChatRequestDeveloperMessage"/>, <see cref="ChatRequestSystemMessage"/>, <see cref="ChatRequestToolMessage"/> and <see cref="ChatRequestUserMessage"/>.
-        /// </param>
-        /// <param name="frequencyPenalty">
-        /// A value that influences the probability of generated tokens appearing based on their cumulative
-        /// frequency in generated text.
-        /// Positive values will make tokens less likely to appear as their frequency increases and
-        /// decrease the likelihood of the model repeating the same statements verbatim.
-        /// Supported range is [-2, 2].
-        /// </param>
-        /// <param name="internalShouldStreamResponse"> A value indicating whether chat completions should be streamed for this request. </param>
-        /// <param name="presencePenalty">
-        /// A value that influences the probability of generated tokens appearing based on their existing
-        /// presence in generated text.
-        /// Positive values will make tokens less likely to appear when they already exist and increase the
-        /// model's likelihood to output new topics.
-        /// Supported range is [-2, 2].
-        /// </param>
-        /// <param name="temperature">
-        /// The sampling temperature to use that controls the apparent creativity of generated completions.
-        /// Higher values will make output more random while lower values will make results more focused
-        /// and deterministic.
-        /// It is not recommended to modify temperature and top_p for the same completions request as the
-        /// interaction of these two settings is difficult to predict.
-        /// Supported range is [0, 1].
-        /// </param>
-        /// <param name="nucleusSamplingFactor">
-        /// An alternative to sampling with temperature called nucleus sampling. This value causes the
-        /// model to consider the results of tokens with the provided probability mass. As an example, a
-        /// value of 0.15 will cause only the tokens comprising the top 15% of probability mass to be
-        /// considered.
-        /// It is not recommended to modify temperature and top_p for the same completions request as the
-        /// interaction of these two settings is difficult to predict.
-        /// Supported range is [0, 1].
-        /// </param>
-        /// <param name="maxTokens"> The maximum number of tokens to generate. </param>
-        /// <param name="responseFormat">
-        /// An object specifying the format that the model must output.
-        ///
-        /// Setting to `{ "type": "json_schema", "json_schema": {...} }` enables Structured Outputs which ensures the model will match your supplied JSON schema.
-        ///
-        /// Setting to `{ "type": "json_object" }` enables JSON mode, which ensures the message the model generates is valid JSON.
-        ///
-        /// **Important:** when using JSON mode, you **must** also instruct the model to produce JSON yourself via a system or user message. Without this, the model may generate an unending stream of whitespace until the generation reaches the token limit, resulting in a long-running and seemingly "stuck" request. Also note that the message content may be partially cut off if `finish_reason="length"`, which indicates the generation exceeded `max_tokens` or the conversation exceeded the max context length.
-        /// Please note <see cref="ChatCompletionsResponseFormat"/> is the base class. According to the scenario, a derived class of the base class might need to be assigned here, or this property needs to be casted to one of the possible derived classes.
-        /// The available derived classes include <see cref="ChatCompletionsResponseFormatJsonObject"/> and <see cref="ChatCompletionsResponseFormatText"/>.
-        /// </param>
-        /// <param name="stopSequences"> A collection of textual sequences that will end completions generation. </param>
-        /// <param name="tools">
-        /// A list of tools the model may request to call. Currently, only functions are supported as a tool. The model
-        /// may response with a function call request and provide the input arguments in JSON format for that function.
-        /// </param>
-        /// <param name="toolChoice"> If specified, the model will configure which of the provided tools it can use for the chat completions response. </param>
-        /// <param name="seed">
-        /// If specified, the system will make a best effort to sample deterministically such that repeated requests with the
-        /// same seed and parameters should return the same result. Determinism is not guaranteed.
-        /// </param>
-        /// <param name="model"> ID of the specific AI model to use, if more than one model is available on the endpoint. </param>
-        /// <param name="additionalProperties"> Additional Properties. </param>
-        internal CompleteRequest(IReadOnlyList<ChatRequestMessage> messages, float? frequencyPenalty, bool? internalShouldStreamResponse, float? presencePenalty, float? temperature, float? nucleusSamplingFactor, int? maxTokens, ChatCompletionsResponseFormat responseFormat, IReadOnlyList<string> stopSequences, IReadOnlyList<ChatCompletionsToolDefinition> tools, BinaryData toolChoice, long? seed, string model, IReadOnlyDictionary<string, BinaryData> additionalProperties)
-        {
-            Messages = messages;
-            FrequencyPenalty = frequencyPenalty;
-            InternalShouldStreamResponse = internalShouldStreamResponse;
-            PresencePenalty = presencePenalty;
-            Temperature = temperature;
-            NucleusSamplingFactor = nucleusSamplingFactor;
-            MaxTokens = maxTokens;
-            ResponseFormat = responseFormat;
-            StopSequences = stopSequences;
-            Tools = tools;
-            ToolChoice = toolChoice;
-            Seed = seed;
-            Model = model;
-            AdditionalProperties = additionalProperties;
-        }
-
-        /// <summary> Initializes a new instance of <see cref="CompleteRequest"/> for deserialization. </summary>
-        internal CompleteRequest()
-        {
-        }
-
-        /// <summary>
-        /// The collection of context messages associated with this chat completions request.
-        /// Typical usage begins with a chat message for the System role that provides instructions for
-        /// the behavior of the assistant, followed by alternating messages between the User and
-        /// Assistant roles.
-        /// Please note <see cref="ChatRequestMessage"/> is the base class. According to the scenario, a derived class of the base class might need to be assigned here, or this property needs to be casted to one of the possible derived classes.
-        /// The available derived classes include <see cref="ChatRequestAssistantMessage"/>, <see cref="ChatRequestDeveloperMessage"/>, <see cref="ChatRequestSystemMessage"/>, <see cref="ChatRequestToolMessage"/> and <see cref="ChatRequestUserMessage"/>.
-        /// </summary>
-        public IReadOnlyList<ChatRequestMessage> Messages { get; }
-        /// <summary>
-        /// A value that influences the probability of generated tokens appearing based on their cumulative
-        /// frequency in generated text.
-        /// Positive values will make tokens less likely to appear as their frequency increases and
-        /// decrease the likelihood of the model repeating the same statements verbatim.
-        /// Supported range is [-2, 2].
-        /// </summary>
-        public float? FrequencyPenalty { get; }
-        /// <summary> A value indicating whether chat completions should be streamed for this request. </summary>
-        public bool? InternalShouldStreamResponse { get; }
-        /// <summary>
-        /// A value that influences the probability of generated tokens appearing based on their existing
-        /// presence in generated text.
-        /// Positive values will make tokens less likely to appear when they already exist and increase the
-        /// model's likelihood to output new topics.
-        /// Supported range is [-2, 2].
-        /// </summary>
-        public float? PresencePenalty { get; }
-        /// <summary>
-        /// The sampling temperature to use that controls the apparent creativity of generated completions.
-        /// Higher values will make output more random while lower values will make results more focused
-        /// and deterministic.
-        /// It is not recommended to modify temperature and top_p for the same completions request as the
-        /// interaction of these two settings is difficult to predict.
-        /// Supported range is [0, 1].
-        /// </summary>
-        public float? Temperature { get; }
-        /// <summary>
-        /// An alternative to sampling with temperature called nucleus sampling. This value causes the
-        /// model to consider the results of tokens with the provided probability mass. As an example, a
-        /// value of 0.15 will cause only the tokens comprising the top 15% of probability mass to be
-        /// considered.
-        /// It is not recommended to modify temperature and top_p for the same completions request as the
-        /// interaction of these two settings is difficult to predict.
-        /// Supported range is [0, 1].
-        /// </summary>
-        public float? NucleusSamplingFactor { get; }
-        /// <summary> The maximum number of tokens to generate. </summary>
-        public int? MaxTokens { get; }
-        /// <summary>
-        /// An object specifying the format that the model must output.
-        ///
-        /// Setting to `{ "type": "json_schema", "json_schema": {...} }` enables Structured Outputs which ensures the model will match your supplied JSON schema.
-        ///
-        /// Setting to `{ "type": "json_object" }` enables JSON mode, which ensures the message the model generates is valid JSON.
-        ///
-        /// **Important:** when using JSON mode, you **must** also instruct the model to produce JSON yourself via a system or user message. Without this, the model may generate an unending stream of whitespace until the generation reaches the token limit, resulting in a long-running and seemingly "stuck" request. Also note that the message content may be partially cut off if `finish_reason="length"`, which indicates the generation exceeded `max_tokens` or the conversation exceeded the max context length.
-        /// Please note <see cref="ChatCompletionsResponseFormat"/> is the base class. According to the scenario, a derived class of the base class might need to be assigned here, or this property needs to be casted to one of the possible derived classes.
-        /// The available derived classes include <see cref="ChatCompletionsResponseFormatJsonObject"/> and <see cref="ChatCompletionsResponseFormatText"/>.
-        /// </summary>
-        public ChatCompletionsResponseFormat ResponseFormat { get; }
-        /// <summary> A collection of textual sequences that will end completions generation. </summary>
-        public IReadOnlyList<string> StopSequences { get; }
-        /// <summary>
-        /// A list of tools the model may request to call. Currently, only functions are supported as a tool. The model
-        /// may response with a function call request and provide the input arguments in JSON format for that function.
-        /// </summary>
-        public IReadOnlyList<ChatCompletionsToolDefinition> Tools { get; }
-        /// <summary>
-        /// If specified, the model will configure which of the provided tools it can use for the chat completions response.
-        /// <para>
-        /// To assign an object to this property use <see cref="BinaryData.FromObjectAsJson{T}(T, System.Text.Json.JsonSerializerOptions?)"/>.
-        /// </para>
-        /// <para>
-        /// To assign an already formatted json string to this property use <see cref="BinaryData.FromString(string)"/>.
-        /// </para>
-        /// <para>
-        /// <remarks>
-        /// Supported types:
-        /// <list type="bullet">
-        /// <item>
-        /// <description><see cref="ChatCompletionsToolChoicePreset"/></description>
-        /// </item>
-        /// <item>
-        /// <description><see cref="ChatCompletionsNamedToolChoice"/></description>
-        /// </item>
-        /// </list>
-        /// </remarks>
-        /// Examples:
-        /// <list type="bullet">
-        /// <item>
-        /// <term>BinaryData.FromObjectAsJson("foo")</term>
-        /// <description>Creates a payload of "foo".</description>
-        /// </item>
-        /// <item>
-        /// <term>BinaryData.FromString("\"foo\"")</term>
-        /// <description>Creates a payload of "foo".</description>
-        /// </item>
-        /// <item>
-        /// <term>BinaryData.FromObjectAsJson(new { key = "value" })</term>
-        /// <description>Creates a payload of { "key": "value" }.</description>
-        /// </item>
-        /// <item>
-        /// <term>BinaryData.FromString("{\"key\": \"value\"}")</term>
-        /// <description>Creates a payload of { "key": "value" }.</description>
-        /// </item>
-        /// </list>
-        /// </para>
-        /// </summary>
-        public BinaryData ToolChoice { get; }
-        /// <summary>
-        /// If specified, the system will make a best effort to sample deterministically such that repeated requests with the
-        /// same seed and parameters should return the same result. Determinism is not guaranteed.
-        /// </summary>
-        public long? Seed { get; }
-        /// <summary> ID of the specific AI model to use, if more than one model is available on the endpoint. </summary>
-        public string Model { get; }
-        /// <summary>
-        /// Additional Properties
-        /// <para>
-        /// To assign an object to the value of this property use <see cref="BinaryData.FromObjectAsJson{T}(T, System.Text.Json.JsonSerializerOptions?)"/>.
-        /// </para>
-        /// <para>
-        /// To assign an already formatted json string to this property use <see cref="BinaryData.FromString(string)"/>.
-        /// </para>
-        /// <para>
-        /// Examples:
-        /// <list type="bullet">
-        /// <item>
-        /// <term>BinaryData.FromObjectAsJson("foo")</term>
-        /// <description>Creates a payload of "foo".</description>
-        /// </item>
-        /// <item>
-        /// <term>BinaryData.FromString("\"foo\"")</term>
-        /// <description>Creates a payload of "foo".</description>
-        /// </item>
-        /// <item>
-        /// <term>BinaryData.FromObjectAsJson(new { key = "value" })</term>
-        /// <description>Creates a payload of { "key": "value" }.</description>
-        /// </item>
-        /// <item>
-        /// <term>BinaryData.FromString("{\"key\": \"value\"}")</term>
-        /// <description>Creates a payload of { "key": "value" }.</description>
-        /// </item>
-        /// </list>
-        /// </para>
-        /// </summary>
-        public IReadOnlyDictionary<string, BinaryData> AdditionalProperties { get; }
-    }
-}
diff --git a/sdk/ai/Azure.AI.Inference/src/Generated/Docs/EmbeddingsClient.xml b/sdk/ai/Azure.AI.Inference/src/Generated/Docs/EmbeddingsClient.xml
deleted file mode 100644
index 54f0260f0b6b..000000000000
--- a/sdk/ai/Azure.AI.Inference/src/Generated/Docs/EmbeddingsClient.xml
+++ /dev/null
@@ -1,101 +0,0 @@
-<?xml version="1.0" encoding="utf-8"?>
-<doc>
-  <members>
-    <member name="GetModelInfoAsync(CancellationToken)">
-      <example>
-This sample shows how to call GetModelInfoAsync.
-<code><![CDATA[
-Uri endpoint = new Uri("<endpoint>");
-AzureKeyCredential credential = new AzureKeyCredential("<key>");
-EmbeddingsClient client = new EmbeddingsClient(endpoint, credential);
-
-Response<ModelInfo> response = await client.GetModelInfoAsync();
-]]></code>
-This sample shows how to call GetModelInfoAsync.
-<code><![CDATA[
-Uri endpoint = new Uri("<endpoint>");
-AzureKeyCredential credential = new AzureKeyCredential("<key>");
-EmbeddingsClient client = new EmbeddingsClient(endpoint, credential);
-
-Response<ModelInfo> response = await client.GetModelInfoAsync();
-]]></code></example>
-    </member>
-    <member name="GetModelInfo(CancellationToken)">
-      <example>
-This sample shows how to call GetModelInfo.
-<code><![CDATA[
-Uri endpoint = new Uri("<endpoint>");
-AzureKeyCredential credential = new AzureKeyCredential("<key>");
-EmbeddingsClient client = new EmbeddingsClient(endpoint, credential);
-
-Response<ModelInfo> response = client.GetModelInfo();
-]]></code>
-This sample shows how to call GetModelInfo.
-<code><![CDATA[
-Uri endpoint = new Uri("<endpoint>");
-AzureKeyCredential credential = new AzureKeyCredential("<key>");
-EmbeddingsClient client = new EmbeddingsClient(endpoint, credential);
-
-Response<ModelInfo> response = client.GetModelInfo();
-]]></code></example>
-    </member>
-    <member name="GetModelInfoAsync(RequestContext)">
-      <example>
-This sample shows how to call GetModelInfoAsync and parse the result.
-<code><![CDATA[
-Uri endpoint = new Uri("<endpoint>");
-AzureKeyCredential credential = new AzureKeyCredential("<key>");
-EmbeddingsClient client = new EmbeddingsClient(endpoint, credential);
-
-Response response = await client.GetModelInfoAsync(null);
-
-JsonElement result = JsonDocument.Parse(response.ContentStream).RootElement;
-Console.WriteLine(result.GetProperty("model_name").ToString());
-Console.WriteLine(result.GetProperty("model_type").ToString());
-Console.WriteLine(result.GetProperty("model_provider_name").ToString());
-]]></code>
-This sample shows how to call GetModelInfoAsync and parse the result.
-<code><![CDATA[
-Uri endpoint = new Uri("<endpoint>");
-AzureKeyCredential credential = new AzureKeyCredential("<key>");
-EmbeddingsClient client = new EmbeddingsClient(endpoint, credential);
-
-Response response = await client.GetModelInfoAsync(null);
-
-JsonElement result = JsonDocument.Parse(response.ContentStream).RootElement;
-Console.WriteLine(result.GetProperty("model_name").ToString());
-Console.WriteLine(result.GetProperty("model_type").ToString());
-Console.WriteLine(result.GetProperty("model_provider_name").ToString());
-]]></code></example>
-    </member>
-    <member name="GetModelInfo(RequestContext)">
-      <example>
-This sample shows how to call GetModelInfo and parse the result.
-<code><![CDATA[
-Uri endpoint = new Uri("<endpoint>");
-AzureKeyCredential credential = new AzureKeyCredential("<key>");
-EmbeddingsClient client = new EmbeddingsClient(endpoint, credential);
-
-Response response = client.GetModelInfo(null);
-
-JsonElement result = JsonDocument.Parse(response.ContentStream).RootElement;
-Console.WriteLine(result.GetProperty("model_name").ToString());
-Console.WriteLine(result.GetProperty("model_type").ToString());
-Console.WriteLine(result.GetProperty("model_provider_name").ToString());
-]]></code>
-This sample shows how to call GetModelInfo and parse the result.
-<code><![CDATA[
-Uri endpoint = new Uri("<endpoint>");
-AzureKeyCredential credential = new AzureKeyCredential("<key>");
-EmbeddingsClient client = new EmbeddingsClient(endpoint, credential);
-
-Response response = client.GetModelInfo(null);
-
-JsonElement result = JsonDocument.Parse(response.ContentStream).RootElement;
-Console.WriteLine(result.GetProperty("model_name").ToString());
-Console.WriteLine(result.GetProperty("model_type").ToString());
-Console.WriteLine(result.GetProperty("model_provider_name").ToString());
-]]></code></example>
-    </member>
-  </members>
-</doc>
\ No newline at end of file
diff --git a/sdk/ai/Azure.AI.Inference/src/Generated/Docs/ImageEmbeddingsClient.xml b/sdk/ai/Azure.AI.Inference/src/Generated/Docs/ImageEmbeddingsClient.xml
deleted file mode 100644
index 280a6ad03aa7..000000000000
--- a/sdk/ai/Azure.AI.Inference/src/Generated/Docs/ImageEmbeddingsClient.xml
+++ /dev/null
@@ -1,101 +0,0 @@
-<?xml version="1.0" encoding="utf-8"?>
-<doc>
-  <members>
-    <member name="GetModelInfoAsync(CancellationToken)">
-      <example>
-This sample shows how to call GetModelInfoAsync.
-<code><![CDATA[
-Uri endpoint = new Uri("<endpoint>");
-AzureKeyCredential credential = new AzureKeyCredential("<key>");
-ImageEmbeddingsClient client = new ImageEmbeddingsClient(endpoint, credential);
-
-Response<ModelInfo> response = await client.GetModelInfoAsync();
-]]></code>
-This sample shows how to call GetModelInfoAsync.
-<code><![CDATA[
-Uri endpoint = new Uri("<endpoint>");
-AzureKeyCredential credential = new AzureKeyCredential("<key>");
-ImageEmbeddingsClient client = new ImageEmbeddingsClient(endpoint, credential);
-
-Response<ModelInfo> response = await client.GetModelInfoAsync();
-]]></code></example>
-    </member>
-    <member name="GetModelInfo(CancellationToken)">
-      <example>
-This sample shows how to call GetModelInfo.
-<code><![CDATA[
-Uri endpoint = new Uri("<endpoint>");
-AzureKeyCredential credential = new AzureKeyCredential("<key>");
-ImageEmbeddingsClient client = new ImageEmbeddingsClient(endpoint, credential);
-
-Response<ModelInfo> response = client.GetModelInfo();
-]]></code>
-This sample shows how to call GetModelInfo.
-<code><![CDATA[
-Uri endpoint = new Uri("<endpoint>");
-AzureKeyCredential credential = new AzureKeyCredential("<key>");
-ImageEmbeddingsClient client = new ImageEmbeddingsClient(endpoint, credential);
-
-Response<ModelInfo> response = client.GetModelInfo();
-]]></code></example>
-    </member>
-    <member name="GetModelInfoAsync(RequestContext)">
-      <example>
-This sample shows how to call GetModelInfoAsync and parse the result.
-<code><![CDATA[
-Uri endpoint = new Uri("<endpoint>");
-AzureKeyCredential credential = new AzureKeyCredential("<key>");
-ImageEmbeddingsClient client = new ImageEmbeddingsClient(endpoint, credential);
-
-Response response = await client.GetModelInfoAsync(null);
-
-JsonElement result = JsonDocument.Parse(response.ContentStream).RootElement;
-Console.WriteLine(result.GetProperty("model_name").ToString());
-Console.WriteLine(result.GetProperty("model_type").ToString());
-Console.WriteLine(result.GetProperty("model_provider_name").ToString());
-]]></code>
-This sample shows how to call GetModelInfoAsync and parse the result.
-<code><![CDATA[
-Uri endpoint = new Uri("<endpoint>");
-AzureKeyCredential credential = new AzureKeyCredential("<key>");
-ImageEmbeddingsClient client = new ImageEmbeddingsClient(endpoint, credential);
-
-Response response = await client.GetModelInfoAsync(null);
-
-JsonElement result = JsonDocument.Parse(response.ContentStream).RootElement;
-Console.WriteLine(result.GetProperty("model_name").ToString());
-Console.WriteLine(result.GetProperty("model_type").ToString());
-Console.WriteLine(result.GetProperty("model_provider_name").ToString());
-]]></code></example>
-    </member>
-    <member name="GetModelInfo(RequestContext)">
-      <example>
-This sample shows how to call GetModelInfo and parse the result.
-<code><![CDATA[
-Uri endpoint = new Uri("<endpoint>");
-AzureKeyCredential credential = new AzureKeyCredential("<key>");
-ImageEmbeddingsClient client = new ImageEmbeddingsClient(endpoint, credential);
-
-Response response = client.GetModelInfo(null);
-
-JsonElement result = JsonDocument.Parse(response.ContentStream).RootElement;
-Console.WriteLine(result.GetProperty("model_name").ToString());
-Console.WriteLine(result.GetProperty("model_type").ToString());
-Console.WriteLine(result.GetProperty("model_provider_name").ToString());
-]]></code>
-This sample shows how to call GetModelInfo and parse the result.
-<code><![CDATA[
-Uri endpoint = new Uri("<endpoint>");
-AzureKeyCredential credential = new AzureKeyCredential("<key>");
-ImageEmbeddingsClient client = new ImageEmbeddingsClient(endpoint, credential);
-
-Response response = client.GetModelInfo(null);
-
-JsonElement result = JsonDocument.Parse(response.ContentStream).RootElement;
-Console.WriteLine(result.GetProperty("model_name").ToString());
-Console.WriteLine(result.GetProperty("model_type").ToString());
-Console.WriteLine(result.GetProperty("model_provider_name").ToString());
-]]></code></example>
-    </member>
-  </members>
-</doc>
\ No newline at end of file
diff --git a/sdk/ai/Azure.AI.Inference/src/Generated/EmbedRequest.Serialization.cs b/sdk/ai/Azure.AI.Inference/src/Generated/EmbedRequest.Serialization.cs
deleted file mode 100644
index a29c2a0b1d5b..000000000000
--- a/sdk/ai/Azure.AI.Inference/src/Generated/EmbedRequest.Serialization.cs
+++ /dev/null
@@ -1,208 +0,0 @@
-// Copyright (c) Microsoft Corporation. All rights reserved.
-// Licensed under the MIT License.
-
-// <auto-generated/>
-
-#nullable disable
-
-using System;
-using System.ClientModel.Primitives;
-using System.Collections.Generic;
-using System.Text.Json;
-using Azure.Core;
-
-namespace Azure.AI.Inference
-{
-    internal partial class EmbedRequest : IUtf8JsonSerializable, IJsonModel<EmbedRequest>
-    {
-        void IUtf8JsonSerializable.Write(Utf8JsonWriter writer) => ((IJsonModel<EmbedRequest>)this).Write(writer, ModelSerializationExtensions.WireOptions);
-
-        void IJsonModel<EmbedRequest>.Write(Utf8JsonWriter writer, ModelReaderWriterOptions options)
-        {
-            writer.WriteStartObject();
-            JsonModelWriteCore(writer, options);
-            writer.WriteEndObject();
-        }
-
-        /// <param name="writer"> The JSON writer. </param>
-        /// <param name="options"> The client options for reading and writing models. </param>
-        protected virtual void JsonModelWriteCore(Utf8JsonWriter writer, ModelReaderWriterOptions options)
-        {
-            var format = options.Format == "W" ? ((IPersistableModel<EmbedRequest>)this).GetFormatFromOptions(options) : options.Format;
-            if (format != "J")
-            {
-                throw new FormatException($"The model {nameof(EmbedRequest)} does not support writing '{format}' format.");
-            }
-
-            writer.WritePropertyName("input"u8);
-            writer.WriteStartArray();
-            foreach (var item in Input)
-            {
-                writer.WriteStringValue(item);
-            }
-            writer.WriteEndArray();
-            if (Optional.IsDefined(Dimensions))
-            {
-                writer.WritePropertyName("dimensions"u8);
-                writer.WriteNumberValue(Dimensions.Value);
-            }
-            if (Optional.IsDefined(EncodingFormat))
-            {
-                writer.WritePropertyName("encoding_format"u8);
-                writer.WriteStringValue(EncodingFormat.Value.ToString());
-            }
-            if (Optional.IsDefined(InputType))
-            {
-                writer.WritePropertyName("input_type"u8);
-                writer.WriteStringValue(InputType.Value.ToString());
-            }
-            if (Optional.IsDefined(Model))
-            {
-                writer.WritePropertyName("model"u8);
-                writer.WriteStringValue(Model);
-            }
-            foreach (var item in AdditionalProperties)
-            {
-                writer.WritePropertyName(item.Key);
-#if NET6_0_OR_GREATER
-				writer.WriteRawValue(item.Value);
-#else
-                using (JsonDocument document = JsonDocument.Parse(item.Value, ModelSerializationExtensions.JsonDocumentOptions))
-                {
-                    JsonSerializer.Serialize(writer, document.RootElement);
-                }
-#endif
-            }
-        }
-
-        EmbedRequest IJsonModel<EmbedRequest>.Create(ref Utf8JsonReader reader, ModelReaderWriterOptions options)
-        {
-            var format = options.Format == "W" ? ((IPersistableModel<EmbedRequest>)this).GetFormatFromOptions(options) : options.Format;
-            if (format != "J")
-            {
-                throw new FormatException($"The model {nameof(EmbedRequest)} does not support reading '{format}' format.");
-            }
-
-            using JsonDocument document = JsonDocument.ParseValue(ref reader);
-            return DeserializeEmbedRequest(document.RootElement, options);
-        }
-
-        internal static EmbedRequest DeserializeEmbedRequest(JsonElement element, ModelReaderWriterOptions options = null)
-        {
-            options ??= ModelSerializationExtensions.WireOptions;
-
-            if (element.ValueKind == JsonValueKind.Null)
-            {
-                return null;
-            }
-            IReadOnlyList<string> input = default;
-            int? dimensions = default;
-            EmbeddingEncodingFormat? encodingFormat = default;
-            EmbeddingInputType? inputType = default;
-            string model = default;
-            IReadOnlyDictionary<string, BinaryData> additionalProperties = default;
-            Dictionary<string, BinaryData> additionalPropertiesDictionary = new Dictionary<string, BinaryData>();
-            foreach (var property in element.EnumerateObject())
-            {
-                if (property.NameEquals("input"u8))
-                {
-                    List<string> array = new List<string>();
-                    foreach (var item in property.Value.EnumerateArray())
-                    {
-                        array.Add(item.GetString());
-                    }
-                    input = array;
-                    continue;
-                }
-                if (property.NameEquals("dimensions"u8))
-                {
-                    if (property.Value.ValueKind == JsonValueKind.Null)
-                    {
-                        continue;
-                    }
-                    dimensions = property.Value.GetInt32();
-                    continue;
-                }
-                if (property.NameEquals("encoding_format"u8))
-                {
-                    if (property.Value.ValueKind == JsonValueKind.Null)
-                    {
-                        continue;
-                    }
-                    encodingFormat = new EmbeddingEncodingFormat(property.Value.GetString());
-                    continue;
-                }
-                if (property.NameEquals("input_type"u8))
-                {
-                    if (property.Value.ValueKind == JsonValueKind.Null)
-                    {
-                        continue;
-                    }
-                    inputType = new EmbeddingInputType(property.Value.GetString());
-                    continue;
-                }
-                if (property.NameEquals("model"u8))
-                {
-                    model = property.Value.GetString();
-                    continue;
-                }
-                additionalPropertiesDictionary.Add(property.Name, BinaryData.FromString(property.Value.GetRawText()));
-            }
-            additionalProperties = additionalPropertiesDictionary;
-            return new EmbedRequest(
-                input,
-                dimensions,
-                encodingFormat,
-                inputType,
-                model,
-                additionalProperties);
-        }
-
-        BinaryData IPersistableModel<EmbedRequest>.Write(ModelReaderWriterOptions options)
-        {
-            var format = options.Format == "W" ? ((IPersistableModel<EmbedRequest>)this).GetFormatFromOptions(options) : options.Format;
-
-            switch (format)
-            {
-                case "J":
-                    return ModelReaderWriter.Write(this, options);
-                default:
-                    throw new FormatException($"The model {nameof(EmbedRequest)} does not support writing '{options.Format}' format.");
-            }
-        }
-
-        EmbedRequest IPersistableModel<EmbedRequest>.Create(BinaryData data, ModelReaderWriterOptions options)
-        {
-            var format = options.Format == "W" ? ((IPersistableModel<EmbedRequest>)this).GetFormatFromOptions(options) : options.Format;
-
-            switch (format)
-            {
-                case "J":
-                    {
-                        using JsonDocument document = JsonDocument.Parse(data, ModelSerializationExtensions.JsonDocumentOptions);
-                        return DeserializeEmbedRequest(document.RootElement, options);
-                    }
-                default:
-                    throw new FormatException($"The model {nameof(EmbedRequest)} does not support reading '{options.Format}' format.");
-            }
-        }
-
-        string IPersistableModel<EmbedRequest>.GetFormatFromOptions(ModelReaderWriterOptions options) => "J";
-
-        /// <summary> Deserializes the model from a raw response. </summary>
-        /// <param name="response"> The response to deserialize the model from. </param>
-        internal static EmbedRequest FromResponse(Response response)
-        {
-            using var document = JsonDocument.Parse(response.Content, ModelSerializationExtensions.JsonDocumentOptions);
-            return DeserializeEmbedRequest(document.RootElement);
-        }
-
-        /// <summary> Convert into a <see cref="RequestContent"/>. </summary>
-        internal virtual RequestContent ToRequestContent()
-        {
-            var content = new Utf8JsonRequestContent();
-            content.JsonWriter.WriteObjectValue(this, ModelSerializationExtensions.WireOptions);
-            return content;
-        }
-    }
-}
diff --git a/sdk/ai/Azure.AI.Inference/src/Generated/EmbedRequest.cs b/sdk/ai/Azure.AI.Inference/src/Generated/EmbedRequest.cs
deleted file mode 100644
index 7fa22a30f281..000000000000
--- a/sdk/ai/Azure.AI.Inference/src/Generated/EmbedRequest.cs
+++ /dev/null
@@ -1,118 +0,0 @@
-// Copyright (c) Microsoft Corporation. All rights reserved.
-// Licensed under the MIT License.
-
-// <auto-generated/>
-
-#nullable disable
-
-using System;
-using System.Collections.Generic;
-using System.Linq;
-
-namespace Azure.AI.Inference
-{
-    /// <summary> The EmbedRequest. </summary>
-    internal partial class EmbedRequest
-    {
-        /// <summary> Initializes a new instance of <see cref="EmbedRequest"/>. </summary>
-        /// <param name="input">
-        /// Input text to embed, encoded as a string or array of tokens.
-        /// To embed multiple inputs in a single request, pass an array
-        /// of strings or array of token arrays.
-        /// </param>
-        /// <exception cref="ArgumentNullException"> <paramref name="input"/> is null. </exception>
-        internal EmbedRequest(IEnumerable<string> input)
-        {
-            Argument.AssertNotNull(input, nameof(input));
-
-            Input = input.ToList();
-            AdditionalProperties = new ChangeTrackingDictionary<string, BinaryData>();
-        }
-
-        /// <summary> Initializes a new instance of <see cref="EmbedRequest"/>. </summary>
-        /// <param name="input">
-        /// Input text to embed, encoded as a string or array of tokens.
-        /// To embed multiple inputs in a single request, pass an array
-        /// of strings or array of token arrays.
-        /// </param>
-        /// <param name="dimensions">
-        /// Optional. The number of dimensions the resulting output embeddings should have.
-        /// Passing null causes the model to use its default value.
-        /// Returns a 422 error if the model doesn't support the value or parameter.
-        /// </param>
-        /// <param name="encodingFormat"> Optional. The desired format for the returned embeddings. </param>
-        /// <param name="inputType">
-        /// Optional. The type of the input.
-        /// Returns a 422 error if the model doesn't support the value or parameter.
-        /// </param>
-        /// <param name="model"> ID of the specific AI model to use, if more than one model is available on the endpoint. </param>
-        /// <param name="additionalProperties"> Additional Properties. </param>
-        internal EmbedRequest(IReadOnlyList<string> input, int? dimensions, EmbeddingEncodingFormat? encodingFormat, EmbeddingInputType? inputType, string model, IReadOnlyDictionary<string, BinaryData> additionalProperties)
-        {
-            Input = input;
-            Dimensions = dimensions;
-            EncodingFormat = encodingFormat;
-            InputType = inputType;
-            Model = model;
-            AdditionalProperties = additionalProperties;
-        }
-
-        /// <summary> Initializes a new instance of <see cref="EmbedRequest"/> for deserialization. </summary>
-        internal EmbedRequest()
-        {
-        }
-
-        /// <summary>
-        /// Input text to embed, encoded as a string or array of tokens.
-        /// To embed multiple inputs in a single request, pass an array
-        /// of strings or array of token arrays.
-        /// </summary>
-        public IReadOnlyList<string> Input { get; }
-        /// <summary>
-        /// Optional. The number of dimensions the resulting output embeddings should have.
-        /// Passing null causes the model to use its default value.
-        /// Returns a 422 error if the model doesn't support the value or parameter.
-        /// </summary>
-        public int? Dimensions { get; }
-        /// <summary> Optional. The desired format for the returned embeddings. </summary>
-        public EmbeddingEncodingFormat? EncodingFormat { get; }
-        /// <summary>
-        /// Optional. The type of the input.
-        /// Returns a 422 error if the model doesn't support the value or parameter.
-        /// </summary>
-        public EmbeddingInputType? InputType { get; }
-        /// <summary> ID of the specific AI model to use, if more than one model is available on the endpoint. </summary>
-        public string Model { get; }
-        /// <summary>
-        /// Additional Properties
-        /// <para>
-        /// To assign an object to the value of this property use <see cref="BinaryData.FromObjectAsJson{T}(T, System.Text.Json.JsonSerializerOptions?)"/>.
-        /// </para>
-        /// <para>
-        /// To assign an already formatted json string to this property use <see cref="BinaryData.FromString(string)"/>.
-        /// </para>
-        /// <para>
-        /// Examples:
-        /// <list type="bullet">
-        /// <item>
-        /// <term>BinaryData.FromObjectAsJson("foo")</term>
-        /// <description>Creates a payload of "foo".</description>
-        /// </item>
-        /// <item>
-        /// <term>BinaryData.FromString("\"foo\"")</term>
-        /// <description>Creates a payload of "foo".</description>
-        /// </item>
-        /// <item>
-        /// <term>BinaryData.FromObjectAsJson(new { key = "value" })</term>
-        /// <description>Creates a payload of { "key": "value" }.</description>
-        /// </item>
-        /// <item>
-        /// <term>BinaryData.FromString("{\"key\": \"value\"}")</term>
-        /// <description>Creates a payload of { "key": "value" }.</description>
-        /// </item>
-        /// </list>
-        /// </para>
-        /// </summary>
-        public IReadOnlyDictionary<string, BinaryData> AdditionalProperties { get; }
-    }
-}
diff --git a/sdk/ai/Azure.AI.Inference/src/Generated/EmbedRequest1.Serialization.cs b/sdk/ai/Azure.AI.Inference/src/Generated/EmbedRequest1.Serialization.cs
deleted file mode 100644
index e1a7cf44f060..000000000000
--- a/sdk/ai/Azure.AI.Inference/src/Generated/EmbedRequest1.Serialization.cs
+++ /dev/null
@@ -1,208 +0,0 @@
-// Copyright (c) Microsoft Corporation. All rights reserved.
-// Licensed under the MIT License.
-
-// <auto-generated/>
-
-#nullable disable
-
-using System;
-using System.ClientModel.Primitives;
-using System.Collections.Generic;
-using System.Text.Json;
-using Azure.Core;
-
-namespace Azure.AI.Inference
-{
-    internal partial class EmbedRequest1 : IUtf8JsonSerializable, IJsonModel<EmbedRequest1>
-    {
-        void IUtf8JsonSerializable.Write(Utf8JsonWriter writer) => ((IJsonModel<EmbedRequest1>)this).Write(writer, ModelSerializationExtensions.WireOptions);
-
-        void IJsonModel<EmbedRequest1>.Write(Utf8JsonWriter writer, ModelReaderWriterOptions options)
-        {
-            writer.WriteStartObject();
-            JsonModelWriteCore(writer, options);
-            writer.WriteEndObject();
-        }
-
-        /// <param name="writer"> The JSON writer. </param>
-        /// <param name="options"> The client options for reading and writing models. </param>
-        protected virtual void JsonModelWriteCore(Utf8JsonWriter writer, ModelReaderWriterOptions options)
-        {
-            var format = options.Format == "W" ? ((IPersistableModel<EmbedRequest1>)this).GetFormatFromOptions(options) : options.Format;
-            if (format != "J")
-            {
-                throw new FormatException($"The model {nameof(EmbedRequest1)} does not support writing '{format}' format.");
-            }
-
-            writer.WritePropertyName("input"u8);
-            writer.WriteStartArray();
-            foreach (var item in Input)
-            {
-                writer.WriteObjectValue(item, options);
-            }
-            writer.WriteEndArray();
-            if (Optional.IsDefined(Dimensions))
-            {
-                writer.WritePropertyName("dimensions"u8);
-                writer.WriteNumberValue(Dimensions.Value);
-            }
-            if (Optional.IsDefined(EncodingFormat))
-            {
-                writer.WritePropertyName("encoding_format"u8);
-                writer.WriteStringValue(EncodingFormat.Value.ToString());
-            }
-            if (Optional.IsDefined(InputType))
-            {
-                writer.WritePropertyName("input_type"u8);
-                writer.WriteStringValue(InputType.Value.ToString());
-            }
-            if (Optional.IsDefined(Model))
-            {
-                writer.WritePropertyName("model"u8);
-                writer.WriteStringValue(Model);
-            }
-            foreach (var item in AdditionalProperties)
-            {
-                writer.WritePropertyName(item.Key);
-#if NET6_0_OR_GREATER
-				writer.WriteRawValue(item.Value);
-#else
-                using (JsonDocument document = JsonDocument.Parse(item.Value, ModelSerializationExtensions.JsonDocumentOptions))
-                {
-                    JsonSerializer.Serialize(writer, document.RootElement);
-                }
-#endif
-            }
-        }
-
-        EmbedRequest1 IJsonModel<EmbedRequest1>.Create(ref Utf8JsonReader reader, ModelReaderWriterOptions options)
-        {
-            var format = options.Format == "W" ? ((IPersistableModel<EmbedRequest1>)this).GetFormatFromOptions(options) : options.Format;
-            if (format != "J")
-            {
-                throw new FormatException($"The model {nameof(EmbedRequest1)} does not support reading '{format}' format.");
-            }
-
-            using JsonDocument document = JsonDocument.ParseValue(ref reader);
-            return DeserializeEmbedRequest1(document.RootElement, options);
-        }
-
-        internal static EmbedRequest1 DeserializeEmbedRequest1(JsonElement element, ModelReaderWriterOptions options = null)
-        {
-            options ??= ModelSerializationExtensions.WireOptions;
-
-            if (element.ValueKind == JsonValueKind.Null)
-            {
-                return null;
-            }
-            IReadOnlyList<ImageEmbeddingInput> input = default;
-            int? dimensions = default;
-            EmbeddingEncodingFormat? encodingFormat = default;
-            EmbeddingInputType? inputType = default;
-            string model = default;
-            IReadOnlyDictionary<string, BinaryData> additionalProperties = default;
-            Dictionary<string, BinaryData> additionalPropertiesDictionary = new Dictionary<string, BinaryData>();
-            foreach (var property in element.EnumerateObject())
-            {
-                if (property.NameEquals("input"u8))
-                {
-                    List<ImageEmbeddingInput> array = new List<ImageEmbeddingInput>();
-                    foreach (var item in property.Value.EnumerateArray())
-                    {
-                        array.Add(ImageEmbeddingInput.DeserializeImageEmbeddingInput(item, options));
-                    }
-                    input = array;
-                    continue;
-                }
-                if (property.NameEquals("dimensions"u8))
-                {
-                    if (property.Value.ValueKind == JsonValueKind.Null)
-                    {
-                        continue;
-                    }
-                    dimensions = property.Value.GetInt32();
-                    continue;
-                }
-                if (property.NameEquals("encoding_format"u8))
-                {
-                    if (property.Value.ValueKind == JsonValueKind.Null)
-                    {
-                        continue;
-                    }
-                    encodingFormat = new EmbeddingEncodingFormat(property.Value.GetString());
-                    continue;
-                }
-                if (property.NameEquals("input_type"u8))
-                {
-                    if (property.Value.ValueKind == JsonValueKind.Null)
-                    {
-                        continue;
-                    }
-                    inputType = new EmbeddingInputType(property.Value.GetString());
-                    continue;
-                }
-                if (property.NameEquals("model"u8))
-                {
-                    model = property.Value.GetString();
-                    continue;
-                }
-                additionalPropertiesDictionary.Add(property.Name, BinaryData.FromString(property.Value.GetRawText()));
-            }
-            additionalProperties = additionalPropertiesDictionary;
-            return new EmbedRequest1(
-                input,
-                dimensions,
-                encodingFormat,
-                inputType,
-                model,
-                additionalProperties);
-        }
-
-        BinaryData IPersistableModel<EmbedRequest1>.Write(ModelReaderWriterOptions options)
-        {
-            var format = options.Format == "W" ? ((IPersistableModel<EmbedRequest1>)this).GetFormatFromOptions(options) : options.Format;
-
-            switch (format)
-            {
-                case "J":
-                    return ModelReaderWriter.Write(this, options);
-                default:
-                    throw new FormatException($"The model {nameof(EmbedRequest1)} does not support writing '{options.Format}' format.");
-            }
-        }
-
-        EmbedRequest1 IPersistableModel<EmbedRequest1>.Create(BinaryData data, ModelReaderWriterOptions options)
-        {
-            var format = options.Format == "W" ? ((IPersistableModel<EmbedRequest1>)this).GetFormatFromOptions(options) : options.Format;
-
-            switch (format)
-            {
-                case "J":
-                    {
-                        using JsonDocument document = JsonDocument.Parse(data, ModelSerializationExtensions.JsonDocumentOptions);
-                        return DeserializeEmbedRequest1(document.RootElement, options);
-                    }
-                default:
-                    throw new FormatException($"The model {nameof(EmbedRequest1)} does not support reading '{options.Format}' format.");
-            }
-        }
-
-        string IPersistableModel<EmbedRequest1>.GetFormatFromOptions(ModelReaderWriterOptions options) => "J";
-
-        /// <summary> Deserializes the model from a raw response. </summary>
-        /// <param name="response"> The response to deserialize the model from. </param>
-        internal static EmbedRequest1 FromResponse(Response response)
-        {
-            using var document = JsonDocument.Parse(response.Content, ModelSerializationExtensions.JsonDocumentOptions);
-            return DeserializeEmbedRequest1(document.RootElement);
-        }
-
-        /// <summary> Convert into a <see cref="RequestContent"/>. </summary>
-        internal virtual RequestContent ToRequestContent()
-        {
-            var content = new Utf8JsonRequestContent();
-            content.JsonWriter.WriteObjectValue(this, ModelSerializationExtensions.WireOptions);
-            return content;
-        }
-    }
-}
diff --git a/sdk/ai/Azure.AI.Inference/src/Generated/EmbedRequest1.cs b/sdk/ai/Azure.AI.Inference/src/Generated/EmbedRequest1.cs
deleted file mode 100644
index f139f3785243..000000000000
--- a/sdk/ai/Azure.AI.Inference/src/Generated/EmbedRequest1.cs
+++ /dev/null
@@ -1,123 +0,0 @@
-// Copyright (c) Microsoft Corporation. All rights reserved.
-// Licensed under the MIT License.
-
-// <auto-generated/>
-
-#nullable disable
-
-using System;
-using System.Collections.Generic;
-using System.Linq;
-
-namespace Azure.AI.Inference
-{
-    /// <summary> The EmbedRequest1. </summary>
-    internal partial class EmbedRequest1
-    {
-        /// <summary> Initializes a new instance of <see cref="EmbedRequest1"/>. </summary>
-        /// <param name="input">
-        /// Input image to embed. To embed multiple inputs in a single request, pass an array.
-        /// The input must not exceed the max input tokens for the model.
-        /// </param>
-        /// <exception cref="ArgumentNullException"> <paramref name="input"/> is null. </exception>
-        internal EmbedRequest1(IEnumerable<ImageEmbeddingInput> input)
-        {
-            Argument.AssertNotNull(input, nameof(input));
-
-            Input = input.ToList();
-            AdditionalProperties = new ChangeTrackingDictionary<string, BinaryData>();
-        }
-
-        /// <summary> Initializes a new instance of <see cref="EmbedRequest1"/>. </summary>
-        /// <param name="input">
-        /// Input image to embed. To embed multiple inputs in a single request, pass an array.
-        /// The input must not exceed the max input tokens for the model.
-        /// </param>
-        /// <param name="dimensions">
-        /// Optional. The number of dimensions the resulting output embeddings should have.
-        /// Passing null causes the model to use its default value.
-        /// Returns a 422 error if the model doesn't support the value or parameter.
-        /// </param>
-        /// <param name="encodingFormat">
-        /// Optional. The number of dimensions the resulting output embeddings should have.
-        /// Passing null causes the model to use its default value.
-        /// Returns a 422 error if the model doesn't support the value or parameter.
-        /// </param>
-        /// <param name="inputType">
-        /// Optional. The type of the input.
-        /// Returns a 422 error if the model doesn't support the value or parameter.
-        /// </param>
-        /// <param name="model"> ID of the specific AI model to use, if more than one model is available on the endpoint. </param>
-        /// <param name="additionalProperties"> Additional Properties. </param>
-        internal EmbedRequest1(IReadOnlyList<ImageEmbeddingInput> input, int? dimensions, EmbeddingEncodingFormat? encodingFormat, EmbeddingInputType? inputType, string model, IReadOnlyDictionary<string, BinaryData> additionalProperties)
-        {
-            Input = input;
-            Dimensions = dimensions;
-            EncodingFormat = encodingFormat;
-            InputType = inputType;
-            Model = model;
-            AdditionalProperties = additionalProperties;
-        }
-
-        /// <summary> Initializes a new instance of <see cref="EmbedRequest1"/> for deserialization. </summary>
-        internal EmbedRequest1()
-        {
-        }
-
-        /// <summary>
-        /// Input image to embed. To embed multiple inputs in a single request, pass an array.
-        /// The input must not exceed the max input tokens for the model.
-        /// </summary>
-        public IReadOnlyList<ImageEmbeddingInput> Input { get; }
-        /// <summary>
-        /// Optional. The number of dimensions the resulting output embeddings should have.
-        /// Passing null causes the model to use its default value.
-        /// Returns a 422 error if the model doesn't support the value or parameter.
-        /// </summary>
-        public int? Dimensions { get; }
-        /// <summary>
-        /// Optional. The number of dimensions the resulting output embeddings should have.
-        /// Passing null causes the model to use its default value.
-        /// Returns a 422 error if the model doesn't support the value or parameter.
-        /// </summary>
-        public EmbeddingEncodingFormat? EncodingFormat { get; }
-        /// <summary>
-        /// Optional. The type of the input.
-        /// Returns a 422 error if the model doesn't support the value or parameter.
-        /// </summary>
-        public EmbeddingInputType? InputType { get; }
-        /// <summary> ID of the specific AI model to use, if more than one model is available on the endpoint. </summary>
-        public string Model { get; }
-        /// <summary>
-        /// Additional Properties
-        /// <para>
-        /// To assign an object to the value of this property use <see cref="BinaryData.FromObjectAsJson{T}(T, System.Text.Json.JsonSerializerOptions?)"/>.
-        /// </para>
-        /// <para>
-        /// To assign an already formatted json string to this property use <see cref="BinaryData.FromString(string)"/>.
-        /// </para>
-        /// <para>
-        /// Examples:
-        /// <list type="bullet">
-        /// <item>
-        /// <term>BinaryData.FromObjectAsJson("foo")</term>
-        /// <description>Creates a payload of "foo".</description>
-        /// </item>
-        /// <item>
-        /// <term>BinaryData.FromString("\"foo\"")</term>
-        /// <description>Creates a payload of "foo".</description>
-        /// </item>
-        /// <item>
-        /// <term>BinaryData.FromObjectAsJson(new { key = "value" })</term>
-        /// <description>Creates a payload of { "key": "value" }.</description>
-        /// </item>
-        /// <item>
-        /// <term>BinaryData.FromString("{\"key\": \"value\"}")</term>
-        /// <description>Creates a payload of { "key": "value" }.</description>
-        /// </item>
-        /// </list>
-        /// </para>
-        /// </summary>
-        public IReadOnlyDictionary<string, BinaryData> AdditionalProperties { get; }
-    }
-}
diff --git a/sdk/ai/Azure.AI.Inference/src/Generated/EmbeddingEncodingFormat.cs b/sdk/ai/Azure.AI.Inference/src/Generated/EmbeddingEncodingFormat.cs
deleted file mode 100644
index 968dfae30f12..000000000000
--- a/sdk/ai/Azure.AI.Inference/src/Generated/EmbeddingEncodingFormat.cs
+++ /dev/null
@@ -1,60 +0,0 @@
-// Copyright (c) Microsoft Corporation. All rights reserved.
-// Licensed under the MIT License.
-
-// <auto-generated/>
-
-#nullable disable
-
-using System;
-using System.ComponentModel;
-
-namespace Azure.AI.Inference
-{
-    /// <summary>
-    /// The format of the embeddings result.
-    /// Returns a 422 error if the model doesn't support the value or parameter.
-    /// </summary>
-    public readonly partial struct EmbeddingEncodingFormat : IEquatable<EmbeddingEncodingFormat>
-    {
-        private readonly string _value;
-
-        /// <summary> Initializes a new instance of <see cref="EmbeddingEncodingFormat"/>. </summary>
-        /// <exception cref="ArgumentNullException"> <paramref name="value"/> is null. </exception>
-        public EmbeddingEncodingFormat(string value)
-        {
-            _value = value ?? throw new ArgumentNullException(nameof(value));
-        }
-
-        private const string Base64Value = "base64";
-        private const string BinaryValue = "binary";
-        private const string SingleValue = "float";
-        private const string SByteValue = "int8";
-        private const string UbinaryValue = "ubinary";
-        private const string ByteValue = "uint8";
-
-        /// <summary> Base64. </summary>
-        public static EmbeddingEncodingFormat Base64 { get; } = new EmbeddingEncodingFormat(Base64Value);
-        /// <summary> Binary. </summary>
-        public static EmbeddingEncodingFormat Binary { get; } = new EmbeddingEncodingFormat(BinaryValue);
-        /// <summary> ubinary. </summary>
-        public static EmbeddingEncodingFormat Ubinary { get; } = new EmbeddingEncodingFormat(UbinaryValue);
-        /// <summary> Determines if two <see cref="EmbeddingEncodingFormat"/> values are the same. </summary>
-        public static bool operator ==(EmbeddingEncodingFormat left, EmbeddingEncodingFormat right) => left.Equals(right);
-        /// <summary> Determines if two <see cref="EmbeddingEncodingFormat"/> values are not the same. </summary>
-        public static bool operator !=(EmbeddingEncodingFormat left, EmbeddingEncodingFormat right) => !left.Equals(right);
-        /// <summary> Converts a <see cref="string"/> to a <see cref="EmbeddingEncodingFormat"/>. </summary>
-        public static implicit operator EmbeddingEncodingFormat(string value) => new EmbeddingEncodingFormat(value);
-
-        /// <inheritdoc />
-        [EditorBrowsable(EditorBrowsableState.Never)]
-        public override bool Equals(object obj) => obj is EmbeddingEncodingFormat other && Equals(other);
-        /// <inheritdoc />
-        public bool Equals(EmbeddingEncodingFormat other) => string.Equals(_value, other._value, StringComparison.InvariantCultureIgnoreCase);
-
-        /// <inheritdoc />
-        [EditorBrowsable(EditorBrowsableState.Never)]
-        public override int GetHashCode() => _value != null ? StringComparer.InvariantCultureIgnoreCase.GetHashCode(_value) : 0;
-        /// <inheritdoc />
-        public override string ToString() => _value;
-    }
-}
diff --git a/sdk/ai/Azure.AI.Inference/src/Generated/EmbeddingInputType.cs b/sdk/ai/Azure.AI.Inference/src/Generated/EmbeddingInputType.cs
deleted file mode 100644
index 9e75eba6dc3c..000000000000
--- a/sdk/ai/Azure.AI.Inference/src/Generated/EmbeddingInputType.cs
+++ /dev/null
@@ -1,54 +0,0 @@
-// Copyright (c) Microsoft Corporation. All rights reserved.
-// Licensed under the MIT License.
-
-// <auto-generated/>
-
-#nullable disable
-
-using System;
-using System.ComponentModel;
-
-namespace Azure.AI.Inference
-{
-    /// <summary> Represents the input types used for embedding search. </summary>
-    public readonly partial struct EmbeddingInputType : IEquatable<EmbeddingInputType>
-    {
-        private readonly string _value;
-
-        /// <summary> Initializes a new instance of <see cref="EmbeddingInputType"/>. </summary>
-        /// <exception cref="ArgumentNullException"> <paramref name="value"/> is null. </exception>
-        public EmbeddingInputType(string value)
-        {
-            _value = value ?? throw new ArgumentNullException(nameof(value));
-        }
-
-        private const string TextValue = "text";
-        private const string QueryValue = "query";
-        private const string DocumentValue = "document";
-
-        /// <summary> Indicates the input is a general text input. </summary>
-        public static EmbeddingInputType Text { get; } = new EmbeddingInputType(TextValue);
-        /// <summary> Indicates the input represents a search query to find the most relevant documents in your vector database. </summary>
-        public static EmbeddingInputType Query { get; } = new EmbeddingInputType(QueryValue);
-        /// <summary> Indicates the input represents a document that is stored in a vector database. </summary>
-        public static EmbeddingInputType Document { get; } = new EmbeddingInputType(DocumentValue);
-        /// <summary> Determines if two <see cref="EmbeddingInputType"/> values are the same. </summary>
-        public static bool operator ==(EmbeddingInputType left, EmbeddingInputType right) => left.Equals(right);
-        /// <summary> Determines if two <see cref="EmbeddingInputType"/> values are not the same. </summary>
-        public static bool operator !=(EmbeddingInputType left, EmbeddingInputType right) => !left.Equals(right);
-        /// <summary> Converts a <see cref="string"/> to a <see cref="EmbeddingInputType"/>. </summary>
-        public static implicit operator EmbeddingInputType(string value) => new EmbeddingInputType(value);
-
-        /// <inheritdoc />
-        [EditorBrowsable(EditorBrowsableState.Never)]
-        public override bool Equals(object obj) => obj is EmbeddingInputType other && Equals(other);
-        /// <inheritdoc />
-        public bool Equals(EmbeddingInputType other) => string.Equals(_value, other._value, StringComparison.InvariantCultureIgnoreCase);
-
-        /// <inheritdoc />
-        [EditorBrowsable(EditorBrowsableState.Never)]
-        public override int GetHashCode() => _value != null ? StringComparer.InvariantCultureIgnoreCase.GetHashCode(_value) : 0;
-        /// <inheritdoc />
-        public override string ToString() => _value;
-    }
-}
diff --git a/sdk/ai/Azure.AI.Inference/src/Generated/EmbeddingItem.Serialization.cs b/sdk/ai/Azure.AI.Inference/src/Generated/EmbeddingItem.Serialization.cs
deleted file mode 100644
index bedb417a16e3..000000000000
--- a/sdk/ai/Azure.AI.Inference/src/Generated/EmbeddingItem.Serialization.cs
+++ /dev/null
@@ -1,157 +0,0 @@
-// Copyright (c) Microsoft Corporation. All rights reserved.
-// Licensed under the MIT License.
-
-// <auto-generated/>
-
-#nullable disable
-
-using System;
-using System.ClientModel.Primitives;
-using System.Collections.Generic;
-using System.Text.Json;
-using Azure.Core;
-
-namespace Azure.AI.Inference
-{
-    public partial class EmbeddingItem : IUtf8JsonSerializable, IJsonModel<EmbeddingItem>
-    {
-        void IUtf8JsonSerializable.Write(Utf8JsonWriter writer) => ((IJsonModel<EmbeddingItem>)this).Write(writer, ModelSerializationExtensions.WireOptions);
-
-        void IJsonModel<EmbeddingItem>.Write(Utf8JsonWriter writer, ModelReaderWriterOptions options)
-        {
-            writer.WriteStartObject();
-            JsonModelWriteCore(writer, options);
-            writer.WriteEndObject();
-        }
-
-        /// <param name="writer"> The JSON writer. </param>
-        /// <param name="options"> The client options for reading and writing models. </param>
-        protected virtual void JsonModelWriteCore(Utf8JsonWriter writer, ModelReaderWriterOptions options)
-        {
-            var format = options.Format == "W" ? ((IPersistableModel<EmbeddingItem>)this).GetFormatFromOptions(options) : options.Format;
-            if (format != "J")
-            {
-                throw new FormatException($"The model {nameof(EmbeddingItem)} does not support writing '{format}' format.");
-            }
-
-            writer.WritePropertyName("embedding"u8);
-#if NET6_0_OR_GREATER
-				writer.WriteRawValue(Embedding);
-#else
-            using (JsonDocument document = JsonDocument.Parse(Embedding, ModelSerializationExtensions.JsonDocumentOptions))
-            {
-                JsonSerializer.Serialize(writer, document.RootElement);
-            }
-#endif
-            writer.WritePropertyName("index"u8);
-            writer.WriteNumberValue(Index);
-            if (options.Format != "W" && _serializedAdditionalRawData != null)
-            {
-                foreach (var item in _serializedAdditionalRawData)
-                {
-                    writer.WritePropertyName(item.Key);
-#if NET6_0_OR_GREATER
-				writer.WriteRawValue(item.Value);
-#else
-                    using (JsonDocument document = JsonDocument.Parse(item.Value, ModelSerializationExtensions.JsonDocumentOptions))
-                    {
-                        JsonSerializer.Serialize(writer, document.RootElement);
-                    }
-#endif
-                }
-            }
-        }
-
-        EmbeddingItem IJsonModel<EmbeddingItem>.Create(ref Utf8JsonReader reader, ModelReaderWriterOptions options)
-        {
-            var format = options.Format == "W" ? ((IPersistableModel<EmbeddingItem>)this).GetFormatFromOptions(options) : options.Format;
-            if (format != "J")
-            {
-                throw new FormatException($"The model {nameof(EmbeddingItem)} does not support reading '{format}' format.");
-            }
-
-            using JsonDocument document = JsonDocument.ParseValue(ref reader);
-            return DeserializeEmbeddingItem(document.RootElement, options);
-        }
-
-        internal static EmbeddingItem DeserializeEmbeddingItem(JsonElement element, ModelReaderWriterOptions options = null)
-        {
-            options ??= ModelSerializationExtensions.WireOptions;
-
-            if (element.ValueKind == JsonValueKind.Null)
-            {
-                return null;
-            }
-            BinaryData embedding = default;
-            int index = default;
-            IDictionary<string, BinaryData> serializedAdditionalRawData = default;
-            Dictionary<string, BinaryData> rawDataDictionary = new Dictionary<string, BinaryData>();
-            foreach (var property in element.EnumerateObject())
-            {
-                if (property.NameEquals("embedding"u8))
-                {
-                    embedding = BinaryData.FromString(property.Value.GetRawText());
-                    continue;
-                }
-                if (property.NameEquals("index"u8))
-                {
-                    index = property.Value.GetInt32();
-                    continue;
-                }
-                if (options.Format != "W")
-                {
-                    rawDataDictionary.Add(property.Name, BinaryData.FromString(property.Value.GetRawText()));
-                }
-            }
-            serializedAdditionalRawData = rawDataDictionary;
-            return new EmbeddingItem(embedding, index, serializedAdditionalRawData);
-        }
-
-        BinaryData IPersistableModel<EmbeddingItem>.Write(ModelReaderWriterOptions options)
-        {
-            var format = options.Format == "W" ? ((IPersistableModel<EmbeddingItem>)this).GetFormatFromOptions(options) : options.Format;
-
-            switch (format)
-            {
-                case "J":
-                    return ModelReaderWriter.Write(this, options);
-                default:
-                    throw new FormatException($"The model {nameof(EmbeddingItem)} does not support writing '{options.Format}' format.");
-            }
-        }
-
-        EmbeddingItem IPersistableModel<EmbeddingItem>.Create(BinaryData data, ModelReaderWriterOptions options)
-        {
-            var format = options.Format == "W" ? ((IPersistableModel<EmbeddingItem>)this).GetFormatFromOptions(options) : options.Format;
-
-            switch (format)
-            {
-                case "J":
-                    {
-                        using JsonDocument document = JsonDocument.Parse(data, ModelSerializationExtensions.JsonDocumentOptions);
-                        return DeserializeEmbeddingItem(document.RootElement, options);
-                    }
-                default:
-                    throw new FormatException($"The model {nameof(EmbeddingItem)} does not support reading '{options.Format}' format.");
-            }
-        }
-
-        string IPersistableModel<EmbeddingItem>.GetFormatFromOptions(ModelReaderWriterOptions options) => "J";
-
-        /// <summary> Deserializes the model from a raw response. </summary>
-        /// <param name="response"> The response to deserialize the model from. </param>
-        internal static EmbeddingItem FromResponse(Response response)
-        {
-            using var document = JsonDocument.Parse(response.Content, ModelSerializationExtensions.JsonDocumentOptions);
-            return DeserializeEmbeddingItem(document.RootElement);
-        }
-
-        /// <summary> Convert into a <see cref="RequestContent"/>. </summary>
-        internal virtual RequestContent ToRequestContent()
-        {
-            var content = new Utf8JsonRequestContent();
-            content.JsonWriter.WriteObjectValue(this, ModelSerializationExtensions.WireOptions);
-            return content;
-        }
-    }
-}
diff --git a/sdk/ai/Azure.AI.Inference/src/Generated/EmbeddingItem.cs b/sdk/ai/Azure.AI.Inference/src/Generated/EmbeddingItem.cs
deleted file mode 100644
index 676f0aba0bc7..000000000000
--- a/sdk/ai/Azure.AI.Inference/src/Generated/EmbeddingItem.cs
+++ /dev/null
@@ -1,128 +0,0 @@
-// Copyright (c) Microsoft Corporation. All rights reserved.
-// Licensed under the MIT License.
-
-// <auto-generated/>
-
-#nullable disable
-
-using System;
-using System.Collections.Generic;
-
-namespace Azure.AI.Inference
-{
-    /// <summary> Representation of a single embeddings relatedness comparison. </summary>
-    public partial class EmbeddingItem
-    {
-        /// <summary>
-        /// Keeps track of any properties unknown to the library.
-        /// <para>
-        /// To assign an object to the value of this property use <see cref="BinaryData.FromObjectAsJson{T}(T, System.Text.Json.JsonSerializerOptions?)"/>.
-        /// </para>
-        /// <para>
-        /// To assign an already formatted json string to this property use <see cref="BinaryData.FromString(string)"/>.
-        /// </para>
-        /// <para>
-        /// Examples:
-        /// <list type="bullet">
-        /// <item>
-        /// <term>BinaryData.FromObjectAsJson("foo")</term>
-        /// <description>Creates a payload of "foo".</description>
-        /// </item>
-        /// <item>
-        /// <term>BinaryData.FromString("\"foo\"")</term>
-        /// <description>Creates a payload of "foo".</description>
-        /// </item>
-        /// <item>
-        /// <term>BinaryData.FromObjectAsJson(new { key = "value" })</term>
-        /// <description>Creates a payload of { "key": "value" }.</description>
-        /// </item>
-        /// <item>
-        /// <term>BinaryData.FromString("{\"key\": \"value\"}")</term>
-        /// <description>Creates a payload of { "key": "value" }.</description>
-        /// </item>
-        /// </list>
-        /// </para>
-        /// </summary>
-        private IDictionary<string, BinaryData> _serializedAdditionalRawData;
-
-        /// <summary> Initializes a new instance of <see cref="EmbeddingItem"/>. </summary>
-        /// <param name="embedding">
-        /// List of embedding values for the input prompt. These represent a measurement of the
-        /// vector-based relatedness of the provided input. Or a base64 encoded string of the embedding vector.
-        /// </param>
-        /// <param name="index"> Index of the prompt to which the EmbeddingItem corresponds. </param>
-        /// <exception cref="ArgumentNullException"> <paramref name="embedding"/> is null. </exception>
-        internal EmbeddingItem(BinaryData embedding, int index)
-        {
-            Argument.AssertNotNull(embedding, nameof(embedding));
-
-            Embedding = embedding;
-            Index = index;
-        }
-
-        /// <summary> Initializes a new instance of <see cref="EmbeddingItem"/>. </summary>
-        /// <param name="embedding">
-        /// List of embedding values for the input prompt. These represent a measurement of the
-        /// vector-based relatedness of the provided input. Or a base64 encoded string of the embedding vector.
-        /// </param>
-        /// <param name="index"> Index of the prompt to which the EmbeddingItem corresponds. </param>
-        /// <param name="serializedAdditionalRawData"> Keeps track of any properties unknown to the library. </param>
-        internal EmbeddingItem(BinaryData embedding, int index, IDictionary<string, BinaryData> serializedAdditionalRawData)
-        {
-            Embedding = embedding;
-            Index = index;
-            _serializedAdditionalRawData = serializedAdditionalRawData;
-        }
-
-        /// <summary> Initializes a new instance of <see cref="EmbeddingItem"/> for deserialization. </summary>
-        internal EmbeddingItem()
-        {
-        }
-
-        /// <summary>
-        /// List of embedding values for the input prompt. These represent a measurement of the
-        /// vector-based relatedness of the provided input. Or a base64 encoded string of the embedding vector.
-        /// <para>
-        /// To assign an object to this property use <see cref="BinaryData.FromObjectAsJson{T}(T, System.Text.Json.JsonSerializerOptions?)"/>.
-        /// </para>
-        /// <para>
-        /// To assign an already formatted json string to this property use <see cref="BinaryData.FromString(string)"/>.
-        /// </para>
-        /// <para>
-        /// <remarks>
-        /// Supported types:
-        /// <list type="bullet">
-        /// <item>
-        /// <description><see cref="string"/></description>
-        /// </item>
-        /// <item>
-        /// <description><see cref="IList{T}"/> where <c>T</c> is of type <see cref="float"/></description>
-        /// </item>
-        /// </list>
-        /// </remarks>
-        /// Examples:
-        /// <list type="bullet">
-        /// <item>
-        /// <term>BinaryData.FromObjectAsJson("foo")</term>
-        /// <description>Creates a payload of "foo".</description>
-        /// </item>
-        /// <item>
-        /// <term>BinaryData.FromString("\"foo\"")</term>
-        /// <description>Creates a payload of "foo".</description>
-        /// </item>
-        /// <item>
-        /// <term>BinaryData.FromObjectAsJson(new { key = "value" })</term>
-        /// <description>Creates a payload of { "key": "value" }.</description>
-        /// </item>
-        /// <item>
-        /// <term>BinaryData.FromString("{\"key\": \"value\"}")</term>
-        /// <description>Creates a payload of { "key": "value" }.</description>
-        /// </item>
-        /// </list>
-        /// </para>
-        /// </summary>
-        public BinaryData Embedding { get; }
-        /// <summary> Index of the prompt to which the EmbeddingItem corresponds. </summary>
-        public int Index { get; }
-    }
-}
diff --git a/sdk/ai/Azure.AI.Inference/src/Generated/EmbeddingsClient.cs b/sdk/ai/Azure.AI.Inference/src/Generated/EmbeddingsClient.cs
deleted file mode 100644
index 27badd749c53..000000000000
--- a/sdk/ai/Azure.AI.Inference/src/Generated/EmbeddingsClient.cs
+++ /dev/null
@@ -1,230 +0,0 @@
-// Copyright (c) Microsoft Corporation. All rights reserved.
-// Licensed under the MIT License.
-
-// <auto-generated/>
-
-#nullable disable
-
-using System;
-using System.Collections.Generic;
-using System.Linq;
-using System.Threading;
-using System.Threading.Tasks;
-using Azure.Core;
-using Azure.Core.Pipeline;
-
-namespace Azure.AI.Inference
-{
-    // Data plane generated client.
-    /// <summary> The Embeddings service client. </summary>
-    public partial class EmbeddingsClient
-    {
-        private const string AuthorizationHeader = "Authorization";
-        private readonly AzureKeyCredential _keyCredential;
-        private const string AuthorizationApiKeyPrefix = "Bearer";
-        private static readonly string[] AuthorizationScopes = new string[] { "https://ml.azure.com/.default" };
-        private readonly TokenCredential _tokenCredential;
-        private readonly HttpPipeline _pipeline;
-        private readonly Uri _endpoint;
-        private readonly string _apiVersion;
-
-        /// <summary> The ClientDiagnostics is used to provide tracing support for the client library. </summary>
-        internal ClientDiagnostics ClientDiagnostics { get; }
-
-        /// <summary> The HTTP pipeline for sending and receiving REST requests and responses. </summary>
-        public virtual HttpPipeline Pipeline => _pipeline;
-
-        /// <summary> Initializes a new instance of EmbeddingsClient for mocking. </summary>
-        protected EmbeddingsClient()
-        {
-        }
-
-        /// <summary> Initializes a new instance of EmbeddingsClient. </summary>
-        /// <param name="endpoint"> Service host. </param>
-        /// <param name="credential"> A credential used to authenticate to an Azure Service. </param>
-        /// <exception cref="ArgumentNullException"> <paramref name="endpoint"/> or <paramref name="credential"/> is null. </exception>
-        public EmbeddingsClient(Uri endpoint, AzureKeyCredential credential) : this(endpoint, credential, new AzureAIInferenceClientOptions())
-        {
-        }
-
-        /// <summary> Initializes a new instance of EmbeddingsClient. </summary>
-        /// <param name="endpoint"> Service host. </param>
-        /// <param name="credential"> A credential used to authenticate to an Azure Service. </param>
-        /// <exception cref="ArgumentNullException"> <paramref name="endpoint"/> or <paramref name="credential"/> is null. </exception>
-        public EmbeddingsClient(Uri endpoint, TokenCredential credential) : this(endpoint, credential, new AzureAIInferenceClientOptions())
-        {
-        }
-
-        /// <summary> Initializes a new instance of EmbeddingsClient. </summary>
-        /// <param name="endpoint"> Service host. </param>
-        /// <param name="credential"> A credential used to authenticate to an Azure Service. </param>
-        /// <param name="options"> The options for configuring the client. </param>
-        /// <exception cref="ArgumentNullException"> <paramref name="endpoint"/> or <paramref name="credential"/> is null. </exception>
-        public EmbeddingsClient(Uri endpoint, TokenCredential credential, AzureAIInferenceClientOptions options)
-        {
-            Argument.AssertNotNull(endpoint, nameof(endpoint));
-            Argument.AssertNotNull(credential, nameof(credential));
-            options ??= new AzureAIInferenceClientOptions();
-
-            ClientDiagnostics = new ClientDiagnostics(options, true);
-            _tokenCredential = credential;
-            _pipeline = HttpPipelineBuilder.Build(options, Array.Empty<HttpPipelinePolicy>(), new HttpPipelinePolicy[] { new BearerTokenAuthenticationPolicy(_tokenCredential, AuthorizationScopes) }, new ResponseClassifier());
-            _endpoint = endpoint;
-            _apiVersion = options.Version;
-        }
-
-        /// <summary>
-        /// Returns information about the AI model.
-        /// The method makes a REST API call to the `/info` route on the given endpoint.
-        /// This method will only work when using Serverless API or Managed Compute endpoint.
-        /// It will not work for GitHub Models endpoint or Azure OpenAI endpoint.
-        /// </summary>
-        /// <param name="cancellationToken"> The cancellation token to use. </param>
-        /// <include file="Docs/EmbeddingsClient.xml" path="doc/members/member[@name='GetModelInfoAsync(CancellationToken)']/*" />
-        public virtual async Task<Response<ModelInfo>> GetModelInfoAsync(CancellationToken cancellationToken = default)
-        {
-            RequestContext context = FromCancellationToken(cancellationToken);
-            Response response = await GetModelInfoAsync(context).ConfigureAwait(false);
-            return Response.FromValue(ModelInfo.FromResponse(response), response);
-        }
-
-        /// <summary>
-        /// Returns information about the AI model.
-        /// The method makes a REST API call to the `/info` route on the given endpoint.
-        /// This method will only work when using Serverless API or Managed Compute endpoint.
-        /// It will not work for GitHub Models endpoint or Azure OpenAI endpoint.
-        /// </summary>
-        /// <param name="cancellationToken"> The cancellation token to use. </param>
-        /// <include file="Docs/EmbeddingsClient.xml" path="doc/members/member[@name='GetModelInfo(CancellationToken)']/*" />
-        public virtual Response<ModelInfo> GetModelInfo(CancellationToken cancellationToken = default)
-        {
-            RequestContext context = FromCancellationToken(cancellationToken);
-            Response response = GetModelInfo(context);
-            return Response.FromValue(ModelInfo.FromResponse(response), response);
-        }
-
-        /// <summary>
-        /// [Protocol Method] Returns information about the AI model.
-        /// The method makes a REST API call to the `/info` route on the given endpoint.
-        /// This method will only work when using Serverless API or Managed Compute endpoint.
-        /// It will not work for GitHub Models endpoint or Azure OpenAI endpoint.
-        /// <list type="bullet">
-        /// <item>
-        /// <description>
-        /// This <see href="https://github.com/Azure/azure-sdk-for-net/blob/main/sdk/core/Azure.Core/samples/ProtocolMethods.md">protocol method</see> allows explicit creation of the request and processing of the response for advanced scenarios.
-        /// </description>
-        /// </item>
-        /// <item>
-        /// <description>
-        /// Please try the simpler <see cref="GetModelInfoAsync(CancellationToken)"/> convenience overload with strongly typed models first.
-        /// </description>
-        /// </item>
-        /// </list>
-        /// </summary>
-        /// <param name="context"> The request context, which can override default behaviors of the client pipeline on a per-call basis. </param>
-        /// <exception cref="RequestFailedException"> Service returned a non-success status code. </exception>
-        /// <returns> The response returned from the service. </returns>
-        /// <include file="Docs/EmbeddingsClient.xml" path="doc/members/member[@name='GetModelInfoAsync(RequestContext)']/*" />
-        public virtual async Task<Response> GetModelInfoAsync(RequestContext context)
-        {
-            using var scope = ClientDiagnostics.CreateScope("EmbeddingsClient.GetModelInfo");
-            scope.Start();
-            try
-            {
-                using HttpMessage message = CreateGetModelInfoRequest(context);
-                return await _pipeline.ProcessMessageAsync(message, context).ConfigureAwait(false);
-            }
-            catch (Exception e)
-            {
-                scope.Failed(e);
-                throw;
-            }
-        }
-
-        /// <summary>
-        /// [Protocol Method] Returns information about the AI model.
-        /// The method makes a REST API call to the `/info` route on the given endpoint.
-        /// This method will only work when using Serverless API or Managed Compute endpoint.
-        /// It will not work for GitHub Models endpoint or Azure OpenAI endpoint.
-        /// <list type="bullet">
-        /// <item>
-        /// <description>
-        /// This <see href="https://github.com/Azure/azure-sdk-for-net/blob/main/sdk/core/Azure.Core/samples/ProtocolMethods.md">protocol method</see> allows explicit creation of the request and processing of the response for advanced scenarios.
-        /// </description>
-        /// </item>
-        /// <item>
-        /// <description>
-        /// Please try the simpler <see cref="GetModelInfo(CancellationToken)"/> convenience overload with strongly typed models first.
-        /// </description>
-        /// </item>
-        /// </list>
-        /// </summary>
-        /// <param name="context"> The request context, which can override default behaviors of the client pipeline on a per-call basis. </param>
-        /// <exception cref="RequestFailedException"> Service returned a non-success status code. </exception>
-        /// <returns> The response returned from the service. </returns>
-        /// <include file="Docs/EmbeddingsClient.xml" path="doc/members/member[@name='GetModelInfo(RequestContext)']/*" />
-        public virtual Response GetModelInfo(RequestContext context)
-        {
-            using var scope = ClientDiagnostics.CreateScope("EmbeddingsClient.GetModelInfo");
-            scope.Start();
-            try
-            {
-                using HttpMessage message = CreateGetModelInfoRequest(context);
-                return _pipeline.ProcessMessage(message, context);
-            }
-            catch (Exception e)
-            {
-                scope.Failed(e);
-                throw;
-            }
-        }
-
-        internal HttpMessage CreateEmbedRequest(RequestContent content, string extraParams, RequestContext context)
-        {
-            var message = _pipeline.CreateMessage(context, ResponseClassifier200);
-            var request = message.Request;
-            request.Method = RequestMethod.Post;
-            var uri = new RawRequestUriBuilder();
-            uri.Reset(_endpoint);
-            uri.AppendPath("/embeddings", false);
-            uri.AppendQuery("api-version", _apiVersion, true);
-            request.Uri = uri;
-            request.Headers.Add("Accept", "application/json");
-            if (extraParams != null)
-            {
-                request.Headers.Add("extra-parameters", extraParams);
-            }
-            request.Headers.Add("Content-Type", "application/json");
-            request.Content = content;
-            return message;
-        }
-
-        internal HttpMessage CreateGetModelInfoRequest(RequestContext context)
-        {
-            var message = _pipeline.CreateMessage(context, ResponseClassifier200);
-            var request = message.Request;
-            request.Method = RequestMethod.Get;
-            var uri = new RawRequestUriBuilder();
-            uri.Reset(_endpoint);
-            uri.AppendPath("/info", false);
-            uri.AppendQuery("api-version", _apiVersion, true);
-            request.Uri = uri;
-            request.Headers.Add("Accept", "application/json");
-            return message;
-        }
-
-        private static RequestContext DefaultRequestContext = new RequestContext();
-        internal static RequestContext FromCancellationToken(CancellationToken cancellationToken = default)
-        {
-            if (!cancellationToken.CanBeCanceled)
-            {
-                return DefaultRequestContext;
-            }
-
-            return new RequestContext() { CancellationToken = cancellationToken };
-        }
-
-        private static ResponseClassifier _responseClassifier200;
-        private static ResponseClassifier ResponseClassifier200 => _responseClassifier200 ??= new StatusCodeClassifier(stackalloc ushort[] { 200 });
-    }
-}
diff --git a/sdk/ai/Azure.AI.Inference/src/Generated/EmbeddingsOptions.Serialization.cs b/sdk/ai/Azure.AI.Inference/src/Generated/EmbeddingsOptions.Serialization.cs
deleted file mode 100644
index 85641804f737..000000000000
--- a/sdk/ai/Azure.AI.Inference/src/Generated/EmbeddingsOptions.Serialization.cs
+++ /dev/null
@@ -1,208 +0,0 @@
-// Copyright (c) Microsoft Corporation. All rights reserved.
-// Licensed under the MIT License.
-
-// <auto-generated/>
-
-#nullable disable
-
-using System;
-using System.ClientModel.Primitives;
-using System.Collections.Generic;
-using System.Text.Json;
-using Azure.Core;
-
-namespace Azure.AI.Inference
-{
-    public partial class EmbeddingsOptions : IUtf8JsonSerializable, IJsonModel<EmbeddingsOptions>
-    {
-        void IUtf8JsonSerializable.Write(Utf8JsonWriter writer) => ((IJsonModel<EmbeddingsOptions>)this).Write(writer, ModelSerializationExtensions.WireOptions);
-
-        void IJsonModel<EmbeddingsOptions>.Write(Utf8JsonWriter writer, ModelReaderWriterOptions options)
-        {
-            writer.WriteStartObject();
-            JsonModelWriteCore(writer, options);
-            writer.WriteEndObject();
-        }
-
-        /// <param name="writer"> The JSON writer. </param>
-        /// <param name="options"> The client options for reading and writing models. </param>
-        protected virtual void JsonModelWriteCore(Utf8JsonWriter writer, ModelReaderWriterOptions options)
-        {
-            var format = options.Format == "W" ? ((IPersistableModel<EmbeddingsOptions>)this).GetFormatFromOptions(options) : options.Format;
-            if (format != "J")
-            {
-                throw new FormatException($"The model {nameof(EmbeddingsOptions)} does not support writing '{format}' format.");
-            }
-
-            writer.WritePropertyName("input"u8);
-            writer.WriteStartArray();
-            foreach (var item in Input)
-            {
-                writer.WriteStringValue(item);
-            }
-            writer.WriteEndArray();
-            if (Optional.IsDefined(Dimensions))
-            {
-                writer.WritePropertyName("dimensions"u8);
-                writer.WriteNumberValue(Dimensions.Value);
-            }
-            if (Optional.IsDefined(EncodingFormat))
-            {
-                writer.WritePropertyName("encoding_format"u8);
-                writer.WriteStringValue(EncodingFormat.Value.ToString());
-            }
-            if (Optional.IsDefined(InputType))
-            {
-                writer.WritePropertyName("input_type"u8);
-                writer.WriteStringValue(InputType.Value.ToString());
-            }
-            if (Optional.IsDefined(Model))
-            {
-                writer.WritePropertyName("model"u8);
-                writer.WriteStringValue(Model);
-            }
-            foreach (var item in AdditionalProperties)
-            {
-                writer.WritePropertyName(item.Key);
-#if NET6_0_OR_GREATER
-				writer.WriteRawValue(item.Value);
-#else
-                using (JsonDocument document = JsonDocument.Parse(item.Value, ModelSerializationExtensions.JsonDocumentOptions))
-                {
-                    JsonSerializer.Serialize(writer, document.RootElement);
-                }
-#endif
-            }
-        }
-
-        EmbeddingsOptions IJsonModel<EmbeddingsOptions>.Create(ref Utf8JsonReader reader, ModelReaderWriterOptions options)
-        {
-            var format = options.Format == "W" ? ((IPersistableModel<EmbeddingsOptions>)this).GetFormatFromOptions(options) : options.Format;
-            if (format != "J")
-            {
-                throw new FormatException($"The model {nameof(EmbeddingsOptions)} does not support reading '{format}' format.");
-            }
-
-            using JsonDocument document = JsonDocument.ParseValue(ref reader);
-            return DeserializeEmbeddingsOptions(document.RootElement, options);
-        }
-
-        internal static EmbeddingsOptions DeserializeEmbeddingsOptions(JsonElement element, ModelReaderWriterOptions options = null)
-        {
-            options ??= ModelSerializationExtensions.WireOptions;
-
-            if (element.ValueKind == JsonValueKind.Null)
-            {
-                return null;
-            }
-            IList<string> input = default;
-            int? dimensions = default;
-            EmbeddingEncodingFormat? encodingFormat = default;
-            EmbeddingInputType? inputType = default;
-            string model = default;
-            IDictionary<string, BinaryData> additionalProperties = default;
-            Dictionary<string, BinaryData> additionalPropertiesDictionary = new Dictionary<string, BinaryData>();
-            foreach (var property in element.EnumerateObject())
-            {
-                if (property.NameEquals("input"u8))
-                {
-                    List<string> array = new List<string>();
-                    foreach (var item in property.Value.EnumerateArray())
-                    {
-                        array.Add(item.GetString());
-                    }
-                    input = array;
-                    continue;
-                }
-                if (property.NameEquals("dimensions"u8))
-                {
-                    if (property.Value.ValueKind == JsonValueKind.Null)
-                    {
-                        continue;
-                    }
-                    dimensions = property.Value.GetInt32();
-                    continue;
-                }
-                if (property.NameEquals("encoding_format"u8))
-                {
-                    if (property.Value.ValueKind == JsonValueKind.Null)
-                    {
-                        continue;
-                    }
-                    encodingFormat = new EmbeddingEncodingFormat(property.Value.GetString());
-                    continue;
-                }
-                if (property.NameEquals("input_type"u8))
-                {
-                    if (property.Value.ValueKind == JsonValueKind.Null)
-                    {
-                        continue;
-                    }
-                    inputType = new EmbeddingInputType(property.Value.GetString());
-                    continue;
-                }
-                if (property.NameEquals("model"u8))
-                {
-                    model = property.Value.GetString();
-                    continue;
-                }
-                additionalPropertiesDictionary.Add(property.Name, BinaryData.FromString(property.Value.GetRawText()));
-            }
-            additionalProperties = additionalPropertiesDictionary;
-            return new EmbeddingsOptions(
-                input,
-                dimensions,
-                encodingFormat,
-                inputType,
-                model,
-                additionalProperties);
-        }
-
-        BinaryData IPersistableModel<EmbeddingsOptions>.Write(ModelReaderWriterOptions options)
-        {
-            var format = options.Format == "W" ? ((IPersistableModel<EmbeddingsOptions>)this).GetFormatFromOptions(options) : options.Format;
-
-            switch (format)
-            {
-                case "J":
-                    return ModelReaderWriter.Write(this, options);
-                default:
-                    throw new FormatException($"The model {nameof(EmbeddingsOptions)} does not support writing '{options.Format}' format.");
-            }
-        }
-
-        EmbeddingsOptions IPersistableModel<EmbeddingsOptions>.Create(BinaryData data, ModelReaderWriterOptions options)
-        {
-            var format = options.Format == "W" ? ((IPersistableModel<EmbeddingsOptions>)this).GetFormatFromOptions(options) : options.Format;
-
-            switch (format)
-            {
-                case "J":
-                    {
-                        using JsonDocument document = JsonDocument.Parse(data, ModelSerializationExtensions.JsonDocumentOptions);
-                        return DeserializeEmbeddingsOptions(document.RootElement, options);
-                    }
-                default:
-                    throw new FormatException($"The model {nameof(EmbeddingsOptions)} does not support reading '{options.Format}' format.");
-            }
-        }
-
-        string IPersistableModel<EmbeddingsOptions>.GetFormatFromOptions(ModelReaderWriterOptions options) => "J";
-
-        /// <summary> Deserializes the model from a raw response. </summary>
-        /// <param name="response"> The response to deserialize the model from. </param>
-        internal static EmbeddingsOptions FromResponse(Response response)
-        {
-            using var document = JsonDocument.Parse(response.Content, ModelSerializationExtensions.JsonDocumentOptions);
-            return DeserializeEmbeddingsOptions(document.RootElement);
-        }
-
-        /// <summary> Convert into a <see cref="RequestContent"/>. </summary>
-        internal virtual RequestContent ToRequestContent()
-        {
-            var content = new Utf8JsonRequestContent();
-            content.JsonWriter.WriteObjectValue(this, ModelSerializationExtensions.WireOptions);
-            return content;
-        }
-    }
-}
diff --git a/sdk/ai/Azure.AI.Inference/src/Generated/EmbeddingsOptions.cs b/sdk/ai/Azure.AI.Inference/src/Generated/EmbeddingsOptions.cs
deleted file mode 100644
index 879babca6604..000000000000
--- a/sdk/ai/Azure.AI.Inference/src/Generated/EmbeddingsOptions.cs
+++ /dev/null
@@ -1,118 +0,0 @@
-// Copyright (c) Microsoft Corporation. All rights reserved.
-// Licensed under the MIT License.
-
-// <auto-generated/>
-
-#nullable disable
-
-using System;
-using System.Collections.Generic;
-using System.Linq;
-
-namespace Azure.AI.Inference
-{
-    /// <summary> The configuration information for an embeddings request. </summary>
-    public partial class EmbeddingsOptions
-    {
-        /// <summary> Initializes a new instance of <see cref="EmbeddingsOptions"/>. </summary>
-        /// <param name="input">
-        /// Input text to embed, encoded as a string or array of tokens.
-        /// To embed multiple inputs in a single request, pass an array
-        /// of strings or array of token arrays.
-        /// </param>
-        /// <exception cref="ArgumentNullException"> <paramref name="input"/> is null. </exception>
-        public EmbeddingsOptions(IEnumerable<string> input)
-        {
-            Argument.AssertNotNull(input, nameof(input));
-
-            Input = input.ToList();
-            AdditionalProperties = new ChangeTrackingDictionary<string, BinaryData>();
-        }
-
-        /// <summary> Initializes a new instance of <see cref="EmbeddingsOptions"/>. </summary>
-        /// <param name="input">
-        /// Input text to embed, encoded as a string or array of tokens.
-        /// To embed multiple inputs in a single request, pass an array
-        /// of strings or array of token arrays.
-        /// </param>
-        /// <param name="dimensions">
-        /// Optional. The number of dimensions the resulting output embeddings should have.
-        /// Passing null causes the model to use its default value.
-        /// Returns a 422 error if the model doesn't support the value or parameter.
-        /// </param>
-        /// <param name="encodingFormat"> Optional. The desired format for the returned embeddings. </param>
-        /// <param name="inputType">
-        /// Optional. The type of the input.
-        /// Returns a 422 error if the model doesn't support the value or parameter.
-        /// </param>
-        /// <param name="model"> ID of the specific AI model to use, if more than one model is available on the endpoint. </param>
-        /// <param name="additionalProperties"> Additional Properties. </param>
-        internal EmbeddingsOptions(IList<string> input, int? dimensions, EmbeddingEncodingFormat? encodingFormat, EmbeddingInputType? inputType, string model, IDictionary<string, BinaryData> additionalProperties)
-        {
-            Input = input;
-            Dimensions = dimensions;
-            EncodingFormat = encodingFormat;
-            InputType = inputType;
-            Model = model;
-            AdditionalProperties = additionalProperties;
-        }
-
-        /// <summary> Initializes a new instance of <see cref="EmbeddingsOptions"/> for deserialization. </summary>
-        internal EmbeddingsOptions()
-        {
-        }
-
-        /// <summary>
-        /// Input text to embed, encoded as a string or array of tokens.
-        /// To embed multiple inputs in a single request, pass an array
-        /// of strings or array of token arrays.
-        /// </summary>
-        public IList<string> Input { get; }
-        /// <summary>
-        /// Optional. The number of dimensions the resulting output embeddings should have.
-        /// Passing null causes the model to use its default value.
-        /// Returns a 422 error if the model doesn't support the value or parameter.
-        /// </summary>
-        public int? Dimensions { get; set; }
-        /// <summary> Optional. The desired format for the returned embeddings. </summary>
-        public EmbeddingEncodingFormat? EncodingFormat { get; set; }
-        /// <summary>
-        /// Optional. The type of the input.
-        /// Returns a 422 error if the model doesn't support the value or parameter.
-        /// </summary>
-        public EmbeddingInputType? InputType { get; set; }
-        /// <summary> ID of the specific AI model to use, if more than one model is available on the endpoint. </summary>
-        public string Model { get; set; }
-        /// <summary>
-        /// Additional Properties
-        /// <para>
-        /// To assign an object to the value of this property use <see cref="BinaryData.FromObjectAsJson{T}(T, System.Text.Json.JsonSerializerOptions?)"/>.
-        /// </para>
-        /// <para>
-        /// To assign an already formatted json string to this property use <see cref="BinaryData.FromString(string)"/>.
-        /// </para>
-        /// <para>
-        /// Examples:
-        /// <list type="bullet">
-        /// <item>
-        /// <term>BinaryData.FromObjectAsJson("foo")</term>
-        /// <description>Creates a payload of "foo".</description>
-        /// </item>
-        /// <item>
-        /// <term>BinaryData.FromString("\"foo\"")</term>
-        /// <description>Creates a payload of "foo".</description>
-        /// </item>
-        /// <item>
-        /// <term>BinaryData.FromObjectAsJson(new { key = "value" })</term>
-        /// <description>Creates a payload of { "key": "value" }.</description>
-        /// </item>
-        /// <item>
-        /// <term>BinaryData.FromString("{\"key\": \"value\"}")</term>
-        /// <description>Creates a payload of { "key": "value" }.</description>
-        /// </item>
-        /// </list>
-        /// </para>
-        /// </summary>
-        public IDictionary<string, BinaryData> AdditionalProperties { get; }
-    }
-}
diff --git a/sdk/ai/Azure.AI.Inference/src/Generated/EmbeddingsResult.Serialization.cs b/sdk/ai/Azure.AI.Inference/src/Generated/EmbeddingsResult.Serialization.cs
deleted file mode 100644
index fbeae8c0a6ec..000000000000
--- a/sdk/ai/Azure.AI.Inference/src/Generated/EmbeddingsResult.Serialization.cs
+++ /dev/null
@@ -1,176 +0,0 @@
-// Copyright (c) Microsoft Corporation. All rights reserved.
-// Licensed under the MIT License.
-
-// <auto-generated/>
-
-#nullable disable
-
-using System;
-using System.ClientModel.Primitives;
-using System.Collections.Generic;
-using System.Text.Json;
-using Azure.Core;
-
-namespace Azure.AI.Inference
-{
-    public partial class EmbeddingsResult : IUtf8JsonSerializable, IJsonModel<EmbeddingsResult>
-    {
-        void IUtf8JsonSerializable.Write(Utf8JsonWriter writer) => ((IJsonModel<EmbeddingsResult>)this).Write(writer, ModelSerializationExtensions.WireOptions);
-
-        void IJsonModel<EmbeddingsResult>.Write(Utf8JsonWriter writer, ModelReaderWriterOptions options)
-        {
-            writer.WriteStartObject();
-            JsonModelWriteCore(writer, options);
-            writer.WriteEndObject();
-        }
-
-        /// <param name="writer"> The JSON writer. </param>
-        /// <param name="options"> The client options for reading and writing models. </param>
-        protected virtual void JsonModelWriteCore(Utf8JsonWriter writer, ModelReaderWriterOptions options)
-        {
-            var format = options.Format == "W" ? ((IPersistableModel<EmbeddingsResult>)this).GetFormatFromOptions(options) : options.Format;
-            if (format != "J")
-            {
-                throw new FormatException($"The model {nameof(EmbeddingsResult)} does not support writing '{format}' format.");
-            }
-
-            writer.WritePropertyName("id"u8);
-            writer.WriteStringValue(Id);
-            writer.WritePropertyName("data"u8);
-            writer.WriteStartArray();
-            foreach (var item in Data)
-            {
-                writer.WriteObjectValue(item, options);
-            }
-            writer.WriteEndArray();
-            writer.WritePropertyName("usage"u8);
-            writer.WriteObjectValue(Usage, options);
-            writer.WritePropertyName("model"u8);
-            writer.WriteStringValue(Model);
-            if (options.Format != "W" && _serializedAdditionalRawData != null)
-            {
-                foreach (var item in _serializedAdditionalRawData)
-                {
-                    writer.WritePropertyName(item.Key);
-#if NET6_0_OR_GREATER
-				writer.WriteRawValue(item.Value);
-#else
-                    using (JsonDocument document = JsonDocument.Parse(item.Value, ModelSerializationExtensions.JsonDocumentOptions))
-                    {
-                        JsonSerializer.Serialize(writer, document.RootElement);
-                    }
-#endif
-                }
-            }
-        }
-
-        EmbeddingsResult IJsonModel<EmbeddingsResult>.Create(ref Utf8JsonReader reader, ModelReaderWriterOptions options)
-        {
-            var format = options.Format == "W" ? ((IPersistableModel<EmbeddingsResult>)this).GetFormatFromOptions(options) : options.Format;
-            if (format != "J")
-            {
-                throw new FormatException($"The model {nameof(EmbeddingsResult)} does not support reading '{format}' format.");
-            }
-
-            using JsonDocument document = JsonDocument.ParseValue(ref reader);
-            return DeserializeEmbeddingsResult(document.RootElement, options);
-        }
-
-        internal static EmbeddingsResult DeserializeEmbeddingsResult(JsonElement element, ModelReaderWriterOptions options = null)
-        {
-            options ??= ModelSerializationExtensions.WireOptions;
-
-            if (element.ValueKind == JsonValueKind.Null)
-            {
-                return null;
-            }
-            string id = default;
-            IReadOnlyList<EmbeddingItem> data = default;
-            EmbeddingsUsage usage = default;
-            string model = default;
-            IDictionary<string, BinaryData> serializedAdditionalRawData = default;
-            Dictionary<string, BinaryData> rawDataDictionary = new Dictionary<string, BinaryData>();
-            foreach (var property in element.EnumerateObject())
-            {
-                if (property.NameEquals("id"u8))
-                {
-                    id = property.Value.GetString();
-                    continue;
-                }
-                if (property.NameEquals("data"u8))
-                {
-                    List<EmbeddingItem> array = new List<EmbeddingItem>();
-                    foreach (var item in property.Value.EnumerateArray())
-                    {
-                        array.Add(EmbeddingItem.DeserializeEmbeddingItem(item, options));
-                    }
-                    data = array;
-                    continue;
-                }
-                if (property.NameEquals("usage"u8))
-                {
-                    usage = EmbeddingsUsage.DeserializeEmbeddingsUsage(property.Value, options);
-                    continue;
-                }
-                if (property.NameEquals("model"u8))
-                {
-                    model = property.Value.GetString();
-                    continue;
-                }
-                if (options.Format != "W")
-                {
-                    rawDataDictionary.Add(property.Name, BinaryData.FromString(property.Value.GetRawText()));
-                }
-            }
-            serializedAdditionalRawData = rawDataDictionary;
-            return new EmbeddingsResult(id, data, usage, model, serializedAdditionalRawData);
-        }
-
-        BinaryData IPersistableModel<EmbeddingsResult>.Write(ModelReaderWriterOptions options)
-        {
-            var format = options.Format == "W" ? ((IPersistableModel<EmbeddingsResult>)this).GetFormatFromOptions(options) : options.Format;
-
-            switch (format)
-            {
-                case "J":
-                    return ModelReaderWriter.Write(this, options);
-                default:
-                    throw new FormatException($"The model {nameof(EmbeddingsResult)} does not support writing '{options.Format}' format.");
-            }
-        }
-
-        EmbeddingsResult IPersistableModel<EmbeddingsResult>.Create(BinaryData data, ModelReaderWriterOptions options)
-        {
-            var format = options.Format == "W" ? ((IPersistableModel<EmbeddingsResult>)this).GetFormatFromOptions(options) : options.Format;
-
-            switch (format)
-            {
-                case "J":
-                    {
-                        using JsonDocument document = JsonDocument.Parse(data, ModelSerializationExtensions.JsonDocumentOptions);
-                        return DeserializeEmbeddingsResult(document.RootElement, options);
-                    }
-                default:
-                    throw new FormatException($"The model {nameof(EmbeddingsResult)} does not support reading '{options.Format}' format.");
-            }
-        }
-
-        string IPersistableModel<EmbeddingsResult>.GetFormatFromOptions(ModelReaderWriterOptions options) => "J";
-
-        /// <summary> Deserializes the model from a raw response. </summary>
-        /// <param name="response"> The response to deserialize the model from. </param>
-        internal static EmbeddingsResult FromResponse(Response response)
-        {
-            using var document = JsonDocument.Parse(response.Content, ModelSerializationExtensions.JsonDocumentOptions);
-            return DeserializeEmbeddingsResult(document.RootElement);
-        }
-
-        /// <summary> Convert into a <see cref="RequestContent"/>. </summary>
-        internal virtual RequestContent ToRequestContent()
-        {
-            var content = new Utf8JsonRequestContent();
-            content.JsonWriter.WriteObjectValue(this, ModelSerializationExtensions.WireOptions);
-            return content;
-        }
-    }
-}
diff --git a/sdk/ai/Azure.AI.Inference/src/Generated/EmbeddingsResult.cs b/sdk/ai/Azure.AI.Inference/src/Generated/EmbeddingsResult.cs
deleted file mode 100644
index c44b8e64397b..000000000000
--- a/sdk/ai/Azure.AI.Inference/src/Generated/EmbeddingsResult.cs
+++ /dev/null
@@ -1,101 +0,0 @@
-// Copyright (c) Microsoft Corporation. All rights reserved.
-// Licensed under the MIT License.
-
-// <auto-generated/>
-
-#nullable disable
-
-using System;
-using System.Collections.Generic;
-using System.Linq;
-
-namespace Azure.AI.Inference
-{
-    /// <summary>
-    /// Representation of the response data from an embeddings request.
-    /// Embeddings measure the relatedness of text strings and are commonly used for search, clustering,
-    /// recommendations, and other similar scenarios.
-    /// </summary>
-    public partial class EmbeddingsResult
-    {
-        /// <summary>
-        /// Keeps track of any properties unknown to the library.
-        /// <para>
-        /// To assign an object to the value of this property use <see cref="BinaryData.FromObjectAsJson{T}(T, System.Text.Json.JsonSerializerOptions?)"/>.
-        /// </para>
-        /// <para>
-        /// To assign an already formatted json string to this property use <see cref="BinaryData.FromString(string)"/>.
-        /// </para>
-        /// <para>
-        /// Examples:
-        /// <list type="bullet">
-        /// <item>
-        /// <term>BinaryData.FromObjectAsJson("foo")</term>
-        /// <description>Creates a payload of "foo".</description>
-        /// </item>
-        /// <item>
-        /// <term>BinaryData.FromString("\"foo\"")</term>
-        /// <description>Creates a payload of "foo".</description>
-        /// </item>
-        /// <item>
-        /// <term>BinaryData.FromObjectAsJson(new { key = "value" })</term>
-        /// <description>Creates a payload of { "key": "value" }.</description>
-        /// </item>
-        /// <item>
-        /// <term>BinaryData.FromString("{\"key\": \"value\"}")</term>
-        /// <description>Creates a payload of { "key": "value" }.</description>
-        /// </item>
-        /// </list>
-        /// </para>
-        /// </summary>
-        private IDictionary<string, BinaryData> _serializedAdditionalRawData;
-
-        /// <summary> Initializes a new instance of <see cref="EmbeddingsResult"/>. </summary>
-        /// <param name="id"> Unique identifier for the embeddings result. </param>
-        /// <param name="data"> Embedding values for the prompts submitted in the request. </param>
-        /// <param name="usage"> Usage counts for tokens input using the embeddings API. </param>
-        /// <param name="model"> The model ID used to generate this result. </param>
-        /// <exception cref="ArgumentNullException"> <paramref name="id"/>, <paramref name="data"/>, <paramref name="usage"/> or <paramref name="model"/> is null. </exception>
-        internal EmbeddingsResult(string id, IEnumerable<EmbeddingItem> data, EmbeddingsUsage usage, string model)
-        {
-            Argument.AssertNotNull(id, nameof(id));
-            Argument.AssertNotNull(data, nameof(data));
-            Argument.AssertNotNull(usage, nameof(usage));
-            Argument.AssertNotNull(model, nameof(model));
-
-            Id = id;
-            Data = data.ToList();
-            Usage = usage;
-            Model = model;
-        }
-
-        /// <summary> Initializes a new instance of <see cref="EmbeddingsResult"/>. </summary>
-        /// <param name="id"> Unique identifier for the embeddings result. </param>
-        /// <param name="data"> Embedding values for the prompts submitted in the request. </param>
-        /// <param name="usage"> Usage counts for tokens input using the embeddings API. </param>
-        /// <param name="model"> The model ID used to generate this result. </param>
-        /// <param name="serializedAdditionalRawData"> Keeps track of any properties unknown to the library. </param>
-        internal EmbeddingsResult(string id, IReadOnlyList<EmbeddingItem> data, EmbeddingsUsage usage, string model, IDictionary<string, BinaryData> serializedAdditionalRawData)
-        {
-            Id = id;
-            Data = data;
-            Usage = usage;
-            Model = model;
-            _serializedAdditionalRawData = serializedAdditionalRawData;
-        }
-
-        /// <summary> Initializes a new instance of <see cref="EmbeddingsResult"/> for deserialization. </summary>
-        internal EmbeddingsResult()
-        {
-        }
-
-        /// <summary> Unique identifier for the embeddings result. </summary>
-        public string Id { get; }
-        /// <summary> Embedding values for the prompts submitted in the request. </summary>
-        public IReadOnlyList<EmbeddingItem> Data { get; }
-        /// <summary> Usage counts for tokens input using the embeddings API. </summary>
-        public EmbeddingsUsage Usage { get; }
-        /// <summary> The model ID used to generate this result. </summary>
-        public string Model { get; }
-    }
-}
diff --git a/sdk/ai/Azure.AI.Inference/src/Generated/EmbeddingsUsage.Serialization.cs b/sdk/ai/Azure.AI.Inference/src/Generated/EmbeddingsUsage.Serialization.cs
deleted file mode 100644
index 5315f328448a..000000000000
--- a/sdk/ai/Azure.AI.Inference/src/Generated/EmbeddingsUsage.Serialization.cs
+++ /dev/null
@@ -1,150 +0,0 @@
-// Copyright (c) Microsoft Corporation. All rights reserved.
-// Licensed under the MIT License.
-
-// <auto-generated/>
-
-#nullable disable
-
-using System;
-using System.ClientModel.Primitives;
-using System.Collections.Generic;
-using System.Text.Json;
-using Azure.Core;
-
-namespace Azure.AI.Inference
-{
-    public partial class EmbeddingsUsage : IUtf8JsonSerializable, IJsonModel<EmbeddingsUsage>
-    {
-        void IUtf8JsonSerializable.Write(Utf8JsonWriter writer) => ((IJsonModel<EmbeddingsUsage>)this).Write(writer, ModelSerializationExtensions.WireOptions);
-
-        void IJsonModel<EmbeddingsUsage>.Write(Utf8JsonWriter writer, ModelReaderWriterOptions options)
-        {
-            writer.WriteStartObject();
-            JsonModelWriteCore(writer, options);
-            writer.WriteEndObject();
-        }
-
-        /// <param name="writer"> The JSON writer. </param>
-        /// <param name="options"> The client options for reading and writing models. </param>
-        protected virtual void JsonModelWriteCore(Utf8JsonWriter writer, ModelReaderWriterOptions options)
-        {
-            var format = options.Format == "W" ? ((IPersistableModel<EmbeddingsUsage>)this).GetFormatFromOptions(options) : options.Format;
-            if (format != "J")
-            {
-                throw new FormatException($"The model {nameof(EmbeddingsUsage)} does not support writing '{format}' format.");
-            }
-
-            writer.WritePropertyName("prompt_tokens"u8);
-            writer.WriteNumberValue(PromptTokens);
-            writer.WritePropertyName("total_tokens"u8);
-            writer.WriteNumberValue(TotalTokens);
-            if (options.Format != "W" && _serializedAdditionalRawData != null)
-            {
-                foreach (var item in _serializedAdditionalRawData)
-                {
-                    writer.WritePropertyName(item.Key);
-#if NET6_0_OR_GREATER
-				writer.WriteRawValue(item.Value);
-#else
-                    using (JsonDocument document = JsonDocument.Parse(item.Value, ModelSerializationExtensions.JsonDocumentOptions))
-                    {
-                        JsonSerializer.Serialize(writer, document.RootElement);
-                    }
-#endif
-                }
-            }
-        }
-
-        EmbeddingsUsage IJsonModel<EmbeddingsUsage>.Create(ref Utf8JsonReader reader, ModelReaderWriterOptions options)
-        {
-            var format = options.Format == "W" ? ((IPersistableModel<EmbeddingsUsage>)this).GetFormatFromOptions(options) : options.Format;
-            if (format != "J")
-            {
-                throw new FormatException($"The model {nameof(EmbeddingsUsage)} does not support reading '{format}' format.");
-            }
-
-            using JsonDocument document = JsonDocument.ParseValue(ref reader);
-            return DeserializeEmbeddingsUsage(document.RootElement, options);
-        }
-
-        internal static EmbeddingsUsage DeserializeEmbeddingsUsage(JsonElement element, ModelReaderWriterOptions options = null)
-        {
-            options ??= ModelSerializationExtensions.WireOptions;
-
-            if (element.ValueKind == JsonValueKind.Null)
-            {
-                return null;
-            }
-            int promptTokens = default;
-            int totalTokens = default;
-            IDictionary<string, BinaryData> serializedAdditionalRawData = default;
-            Dictionary<string, BinaryData> rawDataDictionary = new Dictionary<string, BinaryData>();
-            foreach (var property in element.EnumerateObject())
-            {
-                if (property.NameEquals("prompt_tokens"u8))
-                {
-                    promptTokens = property.Value.GetInt32();
-                    continue;
-                }
-                if (property.NameEquals("total_tokens"u8))
-                {
-                    totalTokens = property.Value.GetInt32();
-                    continue;
-                }
-                if (options.Format != "W")
-                {
-                    rawDataDictionary.Add(property.Name, BinaryData.FromString(property.Value.GetRawText()));
-                }
-            }
-            serializedAdditionalRawData = rawDataDictionary;
-            return new EmbeddingsUsage(promptTokens, totalTokens, serializedAdditionalRawData);
-        }
-
-        BinaryData IPersistableModel<EmbeddingsUsage>.Write(ModelReaderWriterOptions options)
-        {
-            var format = options.Format == "W" ? ((IPersistableModel<EmbeddingsUsage>)this).GetFormatFromOptions(options) : options.Format;
-
-            switch (format)
-            {
-                case "J":
-                    return ModelReaderWriter.Write(this, options);
-                default:
-                    throw new FormatException($"The model {nameof(EmbeddingsUsage)} does not support writing '{options.Format}' format.");
-            }
-        }
-
-        EmbeddingsUsage IPersistableModel<EmbeddingsUsage>.Create(BinaryData data, ModelReaderWriterOptions options)
-        {
-            var format = options.Format == "W" ? ((IPersistableModel<EmbeddingsUsage>)this).GetFormatFromOptions(options) : options.Format;
-
-            switch (format)
-            {
-                case "J":
-                    {
-                        using JsonDocument document = JsonDocument.Parse(data, ModelSerializationExtensions.JsonDocumentOptions);
-                        return DeserializeEmbeddingsUsage(document.RootElement, options);
-                    }
-                default:
-                    throw new FormatException($"The model {nameof(EmbeddingsUsage)} does not support reading '{options.Format}' format.");
-            }
-        }
-
-        string IPersistableModel<EmbeddingsUsage>.GetFormatFromOptions(ModelReaderWriterOptions options) => "J";
-
-        /// <summary> Deserializes the model from a raw response. </summary>
-        /// <param name="response"> The response to deserialize the model from. </param>
-        internal static EmbeddingsUsage FromResponse(Response response)
-        {
-            using var document = JsonDocument.Parse(response.Content, ModelSerializationExtensions.JsonDocumentOptions);
-            return DeserializeEmbeddingsUsage(document.RootElement);
-        }
-
-        /// <summary> Convert into a <see cref="RequestContent"/>. </summary>
-        internal virtual RequestContent ToRequestContent()
-        {
-            var content = new Utf8JsonRequestContent();
-            content.JsonWriter.WriteObjectValue(this, ModelSerializationExtensions.WireOptions);
-            return content;
-        }
-    }
-}
diff --git a/sdk/ai/Azure.AI.Inference/src/Generated/EmbeddingsUsage.cs b/sdk/ai/Azure.AI.Inference/src/Generated/EmbeddingsUsage.cs
deleted file mode 100644
index f0808a074012..000000000000
--- a/sdk/ai/Azure.AI.Inference/src/Generated/EmbeddingsUsage.cs
+++ /dev/null
@@ -1,87 +0,0 @@
-// Copyright (c) Microsoft Corporation. All rights reserved.
-// Licensed under the MIT License.
-
-// <auto-generated/>
-
-#nullable disable
-
-using System;
-using System.Collections.Generic;
-
-namespace Azure.AI.Inference
-{
-    /// <summary> Measurement of the amount of tokens used in this request and response. </summary>
-    public partial class EmbeddingsUsage
-    {
-        /// <summary>
-        /// Keeps track of any properties unknown to the library.
-        /// <para>
-        /// To assign an object to the value of this property use <see cref="BinaryData.FromObjectAsJson{T}(T, System.Text.Json.JsonSerializerOptions?)"/>.
-        /// </para>
-        /// <para>
-        /// To assign an already formatted json string to this property use <see cref="BinaryData.FromString(string)"/>.
-        /// </para>
-        /// <para>
-        /// Examples:
-        /// <list type="bullet">
-        /// <item>
-        /// <term>BinaryData.FromObjectAsJson("foo")</term>
-        /// <description>Creates a payload of "foo".</description>
-        /// </item>
-        /// <item>
-        /// <term>BinaryData.FromString("\"foo\"")</term>
-        /// <description>Creates a payload of "foo".</description>
-        /// </item>
-        /// <item>
-        /// <term>BinaryData.FromObjectAsJson(new { key = "value" })</term>
-        /// <description>Creates a payload of { "key": "value" }.</description>
-        /// </item>
-        /// <item>
-        /// <term>BinaryData.FromString("{\"key\": \"value\"}")</term>
-        /// <description>Creates a payload of { "key": "value" }.</description>
-        /// </item>
-        /// </list>
-        /// </para>
-        /// </summary>
-        private IDictionary<string, BinaryData> _serializedAdditionalRawData;
-
-        /// <summary> Initializes a new instance of <see cref="EmbeddingsUsage"/>. </summary>
-        /// <param name="promptTokens"> Number of tokens in the request. </param>
-        /// <param name="totalTokens">
-        /// Total number of tokens transacted in this request/response. Should equal the
-        /// number of tokens in the request.
-        /// </param>
-        internal EmbeddingsUsage(int promptTokens, int totalTokens)
-        {
-            PromptTokens = promptTokens;
-            TotalTokens = totalTokens;
-        }
-
-        /// <summary> Initializes a new instance of <see cref="EmbeddingsUsage"/>. </summary>
-        /// <param name="promptTokens"> Number of tokens in the request. </param>
-        /// <param name="totalTokens">
-        /// Total number of tokens transacted in this request/response. Should equal the
-        /// number of tokens in the request.
-        /// </param>
-        /// <param name="serializedAdditionalRawData"> Keeps track of any properties unknown to the library. </param>
-        internal EmbeddingsUsage(int promptTokens, int totalTokens, IDictionary<string, BinaryData> serializedAdditionalRawData)
-        {
-            PromptTokens = promptTokens;
-            TotalTokens = totalTokens;
-            _serializedAdditionalRawData = serializedAdditionalRawData;
-        }
-
-        /// <summary> Initializes a new instance of <see cref="EmbeddingsUsage"/> for deserialization. </summary>
-        internal EmbeddingsUsage()
-        {
-        }
-
-        /// <summary> Number of tokens in the request. </summary>
-        public int PromptTokens { get; }
-        /// <summary>
-        /// Total number of tokens transacted in this request/response. Should equal the
-        /// number of tokens in the request.
-        /// </summary>
-        public int TotalTokens { get; }
-    }
-}
diff --git a/sdk/ai/Azure.AI.Inference/src/Generated/ImageEmbeddingInput.Serialization.cs b/sdk/ai/Azure.AI.Inference/src/Generated/ImageEmbeddingInput.Serialization.cs
deleted file mode 100644
index b9898e808b01..000000000000
--- a/sdk/ai/Azure.AI.Inference/src/Generated/ImageEmbeddingInput.Serialization.cs
+++ /dev/null
@@ -1,153 +0,0 @@
-// Copyright (c) Microsoft Corporation. All rights reserved.
-// Licensed under the MIT License.
-
-// <auto-generated/>
-
-#nullable disable
-
-using System;
-using System.ClientModel.Primitives;
-using System.Collections.Generic;
-using System.Text.Json;
-using Azure.Core;
-
-namespace Azure.AI.Inference
-{
-    public partial class ImageEmbeddingInput : IUtf8JsonSerializable, IJsonModel<ImageEmbeddingInput>
-    {
-        void IUtf8JsonSerializable.Write(Utf8JsonWriter writer) => ((IJsonModel<ImageEmbeddingInput>)this).Write(writer, ModelSerializationExtensions.WireOptions);
-
-        void IJsonModel<ImageEmbeddingInput>.Write(Utf8JsonWriter writer, ModelReaderWriterOptions options)
-        {
-            writer.WriteStartObject();
-            JsonModelWriteCore(writer, options);
-            writer.WriteEndObject();
-        }
-
-        /// <param name="writer"> The JSON writer. </param>
-        /// <param name="options"> The client options for reading and writing models. </param>
-        protected virtual void JsonModelWriteCore(Utf8JsonWriter writer, ModelReaderWriterOptions options)
-        {
-            var format = options.Format == "W" ? ((IPersistableModel<ImageEmbeddingInput>)this).GetFormatFromOptions(options) : options.Format;
-            if (format != "J")
-            {
-                throw new FormatException($"The model {nameof(ImageEmbeddingInput)} does not support writing '{format}' format.");
-            }
-
-            writer.WritePropertyName("image"u8);
-            writer.WriteStringValue(Image);
-            if (Optional.IsDefined(Text))
-            {
-                writer.WritePropertyName("text"u8);
-                writer.WriteStringValue(Text);
-            }
-            if (options.Format != "W" && _serializedAdditionalRawData != null)
-            {
-                foreach (var item in _serializedAdditionalRawData)
-                {
-                    writer.WritePropertyName(item.Key);
-#if NET6_0_OR_GREATER
-				writer.WriteRawValue(item.Value);
-#else
-                    using (JsonDocument document = JsonDocument.Parse(item.Value, ModelSerializationExtensions.JsonDocumentOptions))
-                    {
-                        JsonSerializer.Serialize(writer, document.RootElement);
-                    }
-#endif
-                }
-            }
-        }
-
-        ImageEmbeddingInput IJsonModel<ImageEmbeddingInput>.Create(ref Utf8JsonReader reader, ModelReaderWriterOptions options)
-        {
-            var format = options.Format == "W" ? ((IPersistableModel<ImageEmbeddingInput>)this).GetFormatFromOptions(options) : options.Format;
-            if (format != "J")
-            {
-                throw new FormatException($"The model {nameof(ImageEmbeddingInput)} does not support reading '{format}' format.");
-            }
-
-            using JsonDocument document = JsonDocument.ParseValue(ref reader);
-            return DeserializeImageEmbeddingInput(document.RootElement, options);
-        }
-
-        internal static ImageEmbeddingInput DeserializeImageEmbeddingInput(JsonElement element, ModelReaderWriterOptions options = null)
-        {
-            options ??= ModelSerializationExtensions.WireOptions;
-
-            if (element.ValueKind == JsonValueKind.Null)
-            {
-                return null;
-            }
-            string image = default;
-            string text = default;
-            IDictionary<string, BinaryData> serializedAdditionalRawData = default;
-            Dictionary<string, BinaryData> rawDataDictionary = new Dictionary<string, BinaryData>();
-            foreach (var property in element.EnumerateObject())
-            {
-                if (property.NameEquals("image"u8))
-                {
-                    image = property.Value.GetString();
-                    continue;
-                }
-                if (property.NameEquals("text"u8))
-                {
-                    text = property.Value.GetString();
-                    continue;
-                }
-                if (options.Format != "W")
-                {
-                    rawDataDictionary.Add(property.Name, BinaryData.FromString(property.Value.GetRawText()));
-                }
-            }
-            serializedAdditionalRawData = rawDataDictionary;
-            return new ImageEmbeddingInput(image, text, serializedAdditionalRawData);
-        }
-
-        BinaryData IPersistableModel<ImageEmbeddingInput>.Write(ModelReaderWriterOptions options)
-        {
-            var format = options.Format == "W" ? ((IPersistableModel<ImageEmbeddingInput>)this).GetFormatFromOptions(options) : options.Format;
-
-            switch (format)
-            {
-                case "J":
-                    return ModelReaderWriter.Write(this, options);
-                default:
-                    throw new FormatException($"The model {nameof(ImageEmbeddingInput)} does not support writing '{options.Format}' format.");
-            }
-        }
-
-        ImageEmbeddingInput IPersistableModel<ImageEmbeddingInput>.Create(BinaryData data, ModelReaderWriterOptions options)
-        {
-            var format = options.Format == "W" ? ((IPersistableModel<ImageEmbeddingInput>)this).GetFormatFromOptions(options) : options.Format;
-
-            switch (format)
-            {
-                case "J":
-                    {
-                        using JsonDocument document = JsonDocument.Parse(data, ModelSerializationExtensions.JsonDocumentOptions);
-                        return DeserializeImageEmbeddingInput(document.RootElement, options);
-                    }
-                default:
-                    throw new FormatException($"The model {nameof(ImageEmbeddingInput)} does not support reading '{options.Format}' format.");
-            }
-        }
-
-        string IPersistableModel<ImageEmbeddingInput>.GetFormatFromOptions(ModelReaderWriterOptions options) => "J";
-
-        /// <summary> Deserializes the model from a raw response. </summary>
-        /// <param name="response"> The response to deserialize the model from. </param>
-        internal static ImageEmbeddingInput FromResponse(Response response)
-        {
-            using var document = JsonDocument.Parse(response.Content, ModelSerializationExtensions.JsonDocumentOptions);
-            return DeserializeImageEmbeddingInput(document.RootElement);
-        }
-
-        /// <summary> Convert into a <see cref="RequestContent"/>. </summary>
-        internal virtual RequestContent ToRequestContent()
-        {
-            var content = new Utf8JsonRequestContent();
-            content.JsonWriter.WriteObjectValue(this, ModelSerializationExtensions.WireOptions);
-            return content;
-        }
-    }
-}
diff --git a/sdk/ai/Azure.AI.Inference/src/Generated/ImageEmbeddingInput.cs b/sdk/ai/Azure.AI.Inference/src/Generated/ImageEmbeddingInput.cs
deleted file mode 100644
index 2ac62dd102f2..000000000000
--- a/sdk/ai/Azure.AI.Inference/src/Generated/ImageEmbeddingInput.cs
+++ /dev/null
@@ -1,85 +0,0 @@
-// Copyright (c) Microsoft Corporation. All rights reserved.
-// Licensed under the MIT License.
-
-// <auto-generated/>
-
-#nullable disable
-
-using System;
-using System.Collections.Generic;
-
-namespace Azure.AI.Inference
-{
-    /// <summary> Represents an image with optional text. </summary>
-    public partial class ImageEmbeddingInput
-    {
-        /// <summary>
-        /// Keeps track of any properties unknown to the library.
-        /// <para>
-        /// To assign an object to the value of this property use <see cref="BinaryData.FromObjectAsJson{T}(T, System.Text.Json.JsonSerializerOptions?)"/>.
-        /// </para>
-        /// <para>
-        /// To assign an already formatted json string to this property use <see cref="BinaryData.FromString(string)"/>.
-        /// </para>
-        /// <para>
-        /// Examples:
-        /// <list type="bullet">
-        /// <item>
-        /// <term>BinaryData.FromObjectAsJson("foo")</term>
-        /// <description>Creates a payload of "foo".</description>
-        /// </item>
-        /// <item>
-        /// <term>BinaryData.FromString("\"foo\"")</term>
-        /// <description>Creates a payload of "foo".</description>
-        /// </item>
-        /// <item>
-        /// <term>BinaryData.FromObjectAsJson(new { key = "value" })</term>
-        /// <description>Creates a payload of { "key": "value" }.</description>
-        /// </item>
-        /// <item>
-        /// <term>BinaryData.FromString("{\"key\": \"value\"}")</term>
-        /// <description>Creates a payload of { "key": "value" }.</description>
-        /// </item>
-        /// </list>
-        /// </para>
-        /// </summary>
-        private IDictionary<string, BinaryData> _serializedAdditionalRawData;
-
-        /// <summary> Initializes a new instance of <see cref="ImageEmbeddingInput"/>. </summary>
-        /// <param name="image"> The input image encoded in base64 string as a data URL. Example: `data:image/{format};base64,{data}`. </param>
-        /// <exception cref="ArgumentNullException"> <paramref name="image"/> is null. </exception>
-        public ImageEmbeddingInput(string image)
-        {
-            Argument.AssertNotNull(image, nameof(image));
-
-            Image = image;
-        }
-
-        /// <summary> Initializes a new instance of <see cref="ImageEmbeddingInput"/>. </summary>
-        /// <param name="image"> The input image encoded in base64 string as a data URL. Example: `data:image/{format};base64,{data}`. </param>
-        /// <param name="text">
-        /// Optional. The text input to feed into the model (like DINO, CLIP).
-        /// Returns a 422 error if the model doesn't support the value or parameter.
-        /// </param>
-        /// <param name="serializedAdditionalRawData"> Keeps track of any properties unknown to the library. </param>
-        internal ImageEmbeddingInput(string image, string text, IDictionary<string, BinaryData> serializedAdditionalRawData)
-        {
-            Image = image;
-            Text = text;
-            _serializedAdditionalRawData = serializedAdditionalRawData;
-        }
-
-        /// <summary> Initializes a new instance of <see cref="ImageEmbeddingInput"/> for deserialization. </summary>
-        internal ImageEmbeddingInput()
-        {
-        }
-
-        /// <summary> The input image encoded in base64 string as a data URL. Example: `data:image/{format};base64,{data}`. </summary>
-        public string Image { get; }
-        /// <summary>
-        /// Optional. The text input to feed into the model (like DINO, CLIP).
-        /// Returns a 422 error if the model doesn't support the value or parameter.
-        /// </summary>
-        public string Text { get; set; }
-    }
-}
diff --git a/sdk/ai/Azure.AI.Inference/src/Generated/ImageEmbeddingsClient.cs b/sdk/ai/Azure.AI.Inference/src/Generated/ImageEmbeddingsClient.cs
deleted file mode 100644
index 5af1f48b85ce..000000000000
--- a/sdk/ai/Azure.AI.Inference/src/Generated/ImageEmbeddingsClient.cs
+++ /dev/null
@@ -1,230 +0,0 @@
-// Copyright (c) Microsoft Corporation. All rights reserved.
-// Licensed under the MIT License.
-
-// <auto-generated/>
-
-#nullable disable
-
-using System;
-using System.Collections.Generic;
-using System.Linq;
-using System.Threading;
-using System.Threading.Tasks;
-using Azure.Core;
-using Azure.Core.Pipeline;
-
-namespace Azure.AI.Inference
-{
-    // Data plane generated client.
-    /// <summary> The ImageEmbeddings service client. </summary>
-    public partial class ImageEmbeddingsClient
-    {
-        private const string AuthorizationHeader = "Authorization";
-        private readonly AzureKeyCredential _keyCredential;
-        private const string AuthorizationApiKeyPrefix = "Bearer";
-        private static readonly string[] AuthorizationScopes = new string[] { "https://ml.azure.com/.default" };
-        private readonly TokenCredential _tokenCredential;
-        private readonly HttpPipeline _pipeline;
-        private readonly Uri _endpoint;
-        private readonly string _apiVersion;
-
-        /// <summary> The ClientDiagnostics is used to provide tracing support for the client library. </summary>
-        internal ClientDiagnostics ClientDiagnostics { get; }
-
-        /// <summary> The HTTP pipeline for sending and receiving REST requests and responses. </summary>
-        public virtual HttpPipeline Pipeline => _pipeline;
-
-        /// <summary> Initializes a new instance of ImageEmbeddingsClient for mocking. </summary>
-        protected ImageEmbeddingsClient()
-        {
-        }
-
-        /// <summary> Initializes a new instance of ImageEmbeddingsClient. </summary>
-        /// <param name="endpoint"> Service host. </param>
-        /// <param name="credential"> A credential used to authenticate to an Azure Service. </param>
-        /// <exception cref="ArgumentNullException"> <paramref name="endpoint"/> or <paramref name="credential"/> is null. </exception>
-        public ImageEmbeddingsClient(Uri endpoint, AzureKeyCredential credential) : this(endpoint, credential, new AzureAIInferenceClientOptions())
-        {
-        }
-
-        /// <summary> Initializes a new instance of ImageEmbeddingsClient. </summary>
-        /// <param name="endpoint"> Service host. </param>
-        /// <param name="credential"> A credential used to authenticate to an Azure Service. </param>
-        /// <exception cref="ArgumentNullException"> <paramref name="endpoint"/> or <paramref name="credential"/> is null. </exception>
-        public ImageEmbeddingsClient(Uri endpoint, TokenCredential credential) : this(endpoint, credential, new AzureAIInferenceClientOptions())
-        {
-        }
-
-        /// <summary> Initializes a new instance of ImageEmbeddingsClient. </summary>
-        /// <param name="endpoint"> Service host. </param>
-        /// <param name="credential"> A credential used to authenticate to an Azure Service. </param>
-        /// <param name="options"> The options for configuring the client. </param>
-        /// <exception cref="ArgumentNullException"> <paramref name="endpoint"/> or <paramref name="credential"/> is null. </exception>
-        public ImageEmbeddingsClient(Uri endpoint, TokenCredential credential, AzureAIInferenceClientOptions options)
-        {
-            Argument.AssertNotNull(endpoint, nameof(endpoint));
-            Argument.AssertNotNull(credential, nameof(credential));
-            options ??= new AzureAIInferenceClientOptions();
-
-            ClientDiagnostics = new ClientDiagnostics(options, true);
-            _tokenCredential = credential;
-            _pipeline = HttpPipelineBuilder.Build(options, Array.Empty<HttpPipelinePolicy>(), new HttpPipelinePolicy[] { new BearerTokenAuthenticationPolicy(_tokenCredential, AuthorizationScopes) }, new ResponseClassifier());
-            _endpoint = endpoint;
-            _apiVersion = options.Version;
-        }
-
-        /// <summary>
-        /// Returns information about the AI model.
-        /// The method makes a REST API call to the `/info` route on the given endpoint.
-        /// This method will only work when using Serverless API or Managed Compute endpoint.
-        /// It will not work for GitHub Models endpoint or Azure OpenAI endpoint.
-        /// </summary>
-        /// <param name="cancellationToken"> The cancellation token to use. </param>
-        /// <include file="Docs/ImageEmbeddingsClient.xml" path="doc/members/member[@name='GetModelInfoAsync(CancellationToken)']/*" />
-        public virtual async Task<Response<ModelInfo>> GetModelInfoAsync(CancellationToken cancellationToken = default)
-        {
-            RequestContext context = FromCancellationToken(cancellationToken);
-            Response response = await GetModelInfoAsync(context).ConfigureAwait(false);
-            return Response.FromValue(ModelInfo.FromResponse(response), response);
-        }
-
-        /// <summary>
-        /// Returns information about the AI model.
-        /// The method makes a REST API call to the `/info` route on the given endpoint.
-        /// This method will only work when using Serverless API or Managed Compute endpoint.
-        /// It will not work for GitHub Models endpoint or Azure OpenAI endpoint.
-        /// </summary>
-        /// <param name="cancellationToken"> The cancellation token to use. </param>
-        /// <include file="Docs/ImageEmbeddingsClient.xml" path="doc/members/member[@name='GetModelInfo(CancellationToken)']/*" />
-        public virtual Response<ModelInfo> GetModelInfo(CancellationToken cancellationToken = default)
-        {
-            RequestContext context = FromCancellationToken(cancellationToken);
-            Response response = GetModelInfo(context);
-            return Response.FromValue(ModelInfo.FromResponse(response), response);
-        }
-
-        /// <summary>
-        /// [Protocol Method] Returns information about the AI model.
-        /// The method makes a REST API call to the `/info` route on the given endpoint.
-        /// This method will only work when using Serverless API or Managed Compute endpoint.
-        /// It will not work for GitHub Models endpoint or Azure OpenAI endpoint.
-        /// <list type="bullet">
-        /// <item>
-        /// <description>
-        /// This <see href="https://github.com/Azure/azure-sdk-for-net/blob/main/sdk/core/Azure.Core/samples/ProtocolMethods.md">protocol method</see> allows explicit creation of the request and processing of the response for advanced scenarios.
-        /// </description>
-        /// </item>
-        /// <item>
-        /// <description>
-        /// Please try the simpler <see cref="GetModelInfoAsync(CancellationToken)"/> convenience overload with strongly typed models first.
-        /// </description>
-        /// </item>
-        /// </list>
-        /// </summary>
-        /// <param name="context"> The request context, which can override default behaviors of the client pipeline on a per-call basis. </param>
-        /// <exception cref="RequestFailedException"> Service returned a non-success status code. </exception>
-        /// <returns> The response returned from the service. </returns>
-        /// <include file="Docs/ImageEmbeddingsClient.xml" path="doc/members/member[@name='GetModelInfoAsync(RequestContext)']/*" />
-        public virtual async Task<Response> GetModelInfoAsync(RequestContext context)
-        {
-            using var scope = ClientDiagnostics.CreateScope("ImageEmbeddingsClient.GetModelInfo");
-            scope.Start();
-            try
-            {
-                using HttpMessage message = CreateGetModelInfoRequest(context);
-                return await _pipeline.ProcessMessageAsync(message, context).ConfigureAwait(false);
-            }
-            catch (Exception e)
-            {
-                scope.Failed(e);
-                throw;
-            }
-        }
-
-        /// <summary>
-        /// [Protocol Method] Returns information about the AI model.
-        /// The method makes a REST API call to the `/info` route on the given endpoint.
-        /// This method will only work when using Serverless API or Managed Compute endpoint.
-        /// It will not work for GitHub Models endpoint or Azure OpenAI endpoint.
-        /// <list type="bullet">
-        /// <item>
-        /// <description>
-        /// This <see href="https://github.com/Azure/azure-sdk-for-net/blob/main/sdk/core/Azure.Core/samples/ProtocolMethods.md">protocol method</see> allows explicit creation of the request and processing of the response for advanced scenarios.
-        /// </description>
-        /// </item>
-        /// <item>
-        /// <description>
-        /// Please try the simpler <see cref="GetModelInfo(CancellationToken)"/> convenience overload with strongly typed models first.
-        /// </description>
-        /// </item>
-        /// </list>
-        /// </summary>
-        /// <param name="context"> The request context, which can override default behaviors of the client pipeline on a per-call basis. </param>
-        /// <exception cref="RequestFailedException"> Service returned a non-success status code. </exception>
-        /// <returns> The response returned from the service. </returns>
-        /// <include file="Docs/ImageEmbeddingsClient.xml" path="doc/members/member[@name='GetModelInfo(RequestContext)']/*" />
-        public virtual Response GetModelInfo(RequestContext context)
-        {
-            using var scope = ClientDiagnostics.CreateScope("ImageEmbeddingsClient.GetModelInfo");
-            scope.Start();
-            try
-            {
-                using HttpMessage message = CreateGetModelInfoRequest(context);
-                return _pipeline.ProcessMessage(message, context);
-            }
-            catch (Exception e)
-            {
-                scope.Failed(e);
-                throw;
-            }
-        }
-
-        internal HttpMessage CreateEmbedRequest(RequestContent content, string extraParams, RequestContext context)
-        {
-            var message = _pipeline.CreateMessage(context, ResponseClassifier200);
-            var request = message.Request;
-            request.Method = RequestMethod.Post;
-            var uri = new RawRequestUriBuilder();
-            uri.Reset(_endpoint);
-            uri.AppendPath("/images/embeddings", false);
-            uri.AppendQuery("api-version", _apiVersion, true);
-            request.Uri = uri;
-            request.Headers.Add("Accept", "application/json");
-            if (extraParams != null)
-            {
-                request.Headers.Add("extra-parameters", extraParams);
-            }
-            request.Headers.Add("Content-Type", "application/json");
-            request.Content = content;
-            return message;
-        }
-
-        internal HttpMessage CreateGetModelInfoRequest(RequestContext context)
-        {
-            var message = _pipeline.CreateMessage(context, ResponseClassifier200);
-            var request = message.Request;
-            request.Method = RequestMethod.Get;
-            var uri = new RawRequestUriBuilder();
-            uri.Reset(_endpoint);
-            uri.AppendPath("/info", false);
-            uri.AppendQuery("api-version", _apiVersion, true);
-            request.Uri = uri;
-            request.Headers.Add("Accept", "application/json");
-            return message;
-        }
-
-        private static RequestContext DefaultRequestContext = new RequestContext();
-        internal static RequestContext FromCancellationToken(CancellationToken cancellationToken = default)
-        {
-            if (!cancellationToken.CanBeCanceled)
-            {
-                return DefaultRequestContext;
-            }
-
-            return new RequestContext() { CancellationToken = cancellationToken };
-        }
-
-        private static ResponseClassifier _responseClassifier200;
-        private static ResponseClassifier ResponseClassifier200 => _responseClassifier200 ??= new StatusCodeClassifier(stackalloc ushort[] { 200 });
-    }
-}
diff --git a/sdk/ai/Azure.AI.Inference/src/Generated/ImageEmbeddingsOptions.Serialization.cs b/sdk/ai/Azure.AI.Inference/src/Generated/ImageEmbeddingsOptions.Serialization.cs
deleted file mode 100644
index 9c051c63fb5a..000000000000
--- a/sdk/ai/Azure.AI.Inference/src/Generated/ImageEmbeddingsOptions.Serialization.cs
+++ /dev/null
@@ -1,208 +0,0 @@
-// Copyright (c) Microsoft Corporation. All rights reserved.
-// Licensed under the MIT License.
-
-// <auto-generated/>
-
-#nullable disable
-
-using System;
-using System.ClientModel.Primitives;
-using System.Collections.Generic;
-using System.Text.Json;
-using Azure.Core;
-
-namespace Azure.AI.Inference
-{
-    public partial class ImageEmbeddingsOptions : IUtf8JsonSerializable, IJsonModel<ImageEmbeddingsOptions>
-    {
-        void IUtf8JsonSerializable.Write(Utf8JsonWriter writer) => ((IJsonModel<ImageEmbeddingsOptions>)this).Write(writer, ModelSerializationExtensions.WireOptions);
-
-        void IJsonModel<ImageEmbeddingsOptions>.Write(Utf8JsonWriter writer, ModelReaderWriterOptions options)
-        {
-            writer.WriteStartObject();
-            JsonModelWriteCore(writer, options);
-            writer.WriteEndObject();
-        }
-
-        /// <param name="writer"> The JSON writer. </param>
-        /// <param name="options"> The client options for reading and writing models. </param>
-        protected virtual void JsonModelWriteCore(Utf8JsonWriter writer, ModelReaderWriterOptions options)
-        {
-            var format = options.Format == "W" ? ((IPersistableModel<ImageEmbeddingsOptions>)this).GetFormatFromOptions(options) : options.Format;
-            if (format != "J")
-            {
-                throw new FormatException($"The model {nameof(ImageEmbeddingsOptions)} does not support writing '{format}' format.");
-            }
-
-            writer.WritePropertyName("input"u8);
-            writer.WriteStartArray();
-            foreach (var item in Input)
-            {
-                writer.WriteObjectValue(item, options);
-            }
-            writer.WriteEndArray();
-            if (Optional.IsDefined(Dimensions))
-            {
-                writer.WritePropertyName("dimensions"u8);
-                writer.WriteNumberValue(Dimensions.Value);
-            }
-            if (Optional.IsDefined(EncodingFormat))
-            {
-                writer.WritePropertyName("encoding_format"u8);
-                writer.WriteStringValue(EncodingFormat.Value.ToString());
-            }
-            if (Optional.IsDefined(InputType))
-            {
-                writer.WritePropertyName("input_type"u8);
-                writer.WriteStringValue(InputType.Value.ToString());
-            }
-            if (Optional.IsDefined(Model))
-            {
-                writer.WritePropertyName("model"u8);
-                writer.WriteStringValue(Model);
-            }
-            foreach (var item in AdditionalProperties)
-            {
-                writer.WritePropertyName(item.Key);
-#if NET6_0_OR_GREATER
-				writer.WriteRawValue(item.Value);
-#else
-                using (JsonDocument document = JsonDocument.Parse(item.Value, ModelSerializationExtensions.JsonDocumentOptions))
-                {
-                    JsonSerializer.Serialize(writer, document.RootElement);
-                }
-#endif
-            }
-        }
-
-        ImageEmbeddingsOptions IJsonModel<ImageEmbeddingsOptions>.Create(ref Utf8JsonReader reader, ModelReaderWriterOptions options)
-        {
-            var format = options.Format == "W" ? ((IPersistableModel<ImageEmbeddingsOptions>)this).GetFormatFromOptions(options) : options.Format;
-            if (format != "J")
-            {
-                throw new FormatException($"The model {nameof(ImageEmbeddingsOptions)} does not support reading '{format}' format.");
-            }
-
-            using JsonDocument document = JsonDocument.ParseValue(ref reader);
-            return DeserializeImageEmbeddingsOptions(document.RootElement, options);
-        }
-
-        internal static ImageEmbeddingsOptions DeserializeImageEmbeddingsOptions(JsonElement element, ModelReaderWriterOptions options = null)
-        {
-            options ??= ModelSerializationExtensions.WireOptions;
-
-            if (element.ValueKind == JsonValueKind.Null)
-            {
-                return null;
-            }
-            IList<ImageEmbeddingInput> input = default;
-            int? dimensions = default;
-            EmbeddingEncodingFormat? encodingFormat = default;
-            EmbeddingInputType? inputType = default;
-            string model = default;
-            IDictionary<string, BinaryData> additionalProperties = default;
-            Dictionary<string, BinaryData> additionalPropertiesDictionary = new Dictionary<string, BinaryData>();
-            foreach (var property in element.EnumerateObject())
-            {
-                if (property.NameEquals("input"u8))
-                {
-                    List<ImageEmbeddingInput> array = new List<ImageEmbeddingInput>();
-                    foreach (var item in property.Value.EnumerateArray())
-                    {
-                        array.Add(ImageEmbeddingInput.DeserializeImageEmbeddingInput(item, options));
-                    }
-                    input = array;
-                    continue;
-                }
-                if (property.NameEquals("dimensions"u8))
-                {
-                    if (property.Value.ValueKind == JsonValueKind.Null)
-                    {
-                        continue;
-                    }
-                    dimensions = property.Value.GetInt32();
-                    continue;
-                }
-                if (property.NameEquals("encoding_format"u8))
-                {
-                    if (property.Value.ValueKind == JsonValueKind.Null)
-                    {
-                        continue;
-                    }
-                    encodingFormat = new EmbeddingEncodingFormat(property.Value.GetString());
-                    continue;
-                }
-                if (property.NameEquals("input_type"u8))
-                {
-                    if (property.Value.ValueKind == JsonValueKind.Null)
-                    {
-                        continue;
-                    }
-                    inputType = new EmbeddingInputType(property.Value.GetString());
-                    continue;
-                }
-                if (property.NameEquals("model"u8))
-                {
-                    model = property.Value.GetString();
-                    continue;
-                }
-                additionalPropertiesDictionary.Add(property.Name, BinaryData.FromString(property.Value.GetRawText()));
-            }
-            additionalProperties = additionalPropertiesDictionary;
-            return new ImageEmbeddingsOptions(
-                input,
-                dimensions,
-                encodingFormat,
-                inputType,
-                model,
-                additionalProperties);
-        }
-
-        BinaryData IPersistableModel<ImageEmbeddingsOptions>.Write(ModelReaderWriterOptions options)
-        {
-            var format = options.Format == "W" ? ((IPersistableModel<ImageEmbeddingsOptions>)this).GetFormatFromOptions(options) : options.Format;
-
-            switch (format)
-            {
-                case "J":
-                    return ModelReaderWriter.Write(this, options);
-                default:
-                    throw new FormatException($"The model {nameof(ImageEmbeddingsOptions)} does not support writing '{options.Format}' format.");
-            }
-        }
-
-        ImageEmbeddingsOptions IPersistableModel<ImageEmbeddingsOptions>.Create(BinaryData data, ModelReaderWriterOptions options)
-        {
-            var format = options.Format == "W" ? ((IPersistableModel<ImageEmbeddingsOptions>)this).GetFormatFromOptions(options) : options.Format;
-
-            switch (format)
-            {
-                case "J":
-                    {
-                        using JsonDocument document = JsonDocument.Parse(data, ModelSerializationExtensions.JsonDocumentOptions);
-                        return DeserializeImageEmbeddingsOptions(document.RootElement, options);
-                    }
-                default:
-                    throw new FormatException($"The model {nameof(ImageEmbeddingsOptions)} does not support reading '{options.Format}' format.");
-            }
-        }
-
-        string IPersistableModel<ImageEmbeddingsOptions>.GetFormatFromOptions(ModelReaderWriterOptions options) => "J";
-
-        /// <summary> Deserializes the model from a raw response. </summary>
-        /// <param name="response"> The response to deserialize the model from. </param>
-        internal static ImageEmbeddingsOptions FromResponse(Response response)
-        {
-            using var document = JsonDocument.Parse(response.Content, ModelSerializationExtensions.JsonDocumentOptions);
-            return DeserializeImageEmbeddingsOptions(document.RootElement);
-        }
-
-        /// <summary> Convert into a <see cref="RequestContent"/>. </summary>
-        internal virtual RequestContent ToRequestContent()
-        {
-            var content = new Utf8JsonRequestContent();
-            content.JsonWriter.WriteObjectValue(this, ModelSerializationExtensions.WireOptions);
-            return content;
-        }
-    }
-}
diff --git a/sdk/ai/Azure.AI.Inference/src/Generated/ImageEmbeddingsOptions.cs b/sdk/ai/Azure.AI.Inference/src/Generated/ImageEmbeddingsOptions.cs
deleted file mode 100644
index e4e9a3b5b99f..000000000000
--- a/sdk/ai/Azure.AI.Inference/src/Generated/ImageEmbeddingsOptions.cs
+++ /dev/null
@@ -1,123 +0,0 @@
-// Copyright (c) Microsoft Corporation. All rights reserved.
-// Licensed under the MIT License.
-
-// <auto-generated/>
-
-#nullable disable
-
-using System;
-using System.Collections.Generic;
-using System.Linq;
-
-namespace Azure.AI.Inference
-{
-    /// <summary> The configuration information for an image embeddings request. </summary>
-    public partial class ImageEmbeddingsOptions
-    {
-        /// <summary> Initializes a new instance of <see cref="ImageEmbeddingsOptions"/>. </summary>
-        /// <param name="input">
-        /// Input image to embed. To embed multiple inputs in a single request, pass an array.
-        /// The input must not exceed the max input tokens for the model.
-        /// </param>
-        /// <exception cref="ArgumentNullException"> <paramref name="input"/> is null. </exception>
-        public ImageEmbeddingsOptions(IEnumerable<ImageEmbeddingInput> input)
-        {
-            Argument.AssertNotNull(input, nameof(input));
-
-            Input = input.ToList();
-            AdditionalProperties = new ChangeTrackingDictionary<string, BinaryData>();
-        }
-
-        /// <summary> Initializes a new instance of <see cref="ImageEmbeddingsOptions"/>. </summary>
-        /// <param name="input">
-        /// Input image to embed. To embed multiple inputs in a single request, pass an array.
-        /// The input must not exceed the max input tokens for the model.
-        /// </param>
-        /// <param name="dimensions">
-        /// Optional. The number of dimensions the resulting output embeddings should have.
-        /// Passing null causes the model to use its default value.
-        /// Returns a 422 error if the model doesn't support the value or parameter.
-        /// </param>
-        /// <param name="encodingFormat">
-        /// Optional. The number of dimensions the resulting output embeddings should have.
-        /// Passing null causes the model to use its default value.
-        /// Returns a 422 error if the model doesn't support the value or parameter.
-        /// </param>
-        /// <param name="inputType">
-        /// Optional. The type of the input.
-        /// Returns a 422 error if the model doesn't support the value or parameter.
-        /// </param>
-        /// <param name="model"> ID of the specific AI model to use, if more than one model is available on the endpoint. </param>
-        /// <param name="additionalProperties"> Additional Properties. </param>
-        internal ImageEmbeddingsOptions(IList<ImageEmbeddingInput> input, int? dimensions, EmbeddingEncodingFormat? encodingFormat, EmbeddingInputType? inputType, string model, IDictionary<string, BinaryData> additionalProperties)
-        {
-            Input = input;
-            Dimensions = dimensions;
-            EncodingFormat = encodingFormat;
-            InputType = inputType;
-            Model = model;
-            AdditionalProperties = additionalProperties;
-        }
-
-        /// <summary> Initializes a new instance of <see cref="ImageEmbeddingsOptions"/> for deserialization. </summary>
-        internal ImageEmbeddingsOptions()
-        {
-        }
-
-        /// <summary>
-        /// Input image to embed. To embed multiple inputs in a single request, pass an array.
-        /// The input must not exceed the max input tokens for the model.
-        /// </summary>
-        public IList<ImageEmbeddingInput> Input { get; }
-        /// <summary>
-        /// Optional. The number of dimensions the resulting output embeddings should have.
-        /// Passing null causes the model to use its default value.
-        /// Returns a 422 error if the model doesn't support the value or parameter.
-        /// </summary>
-        public int? Dimensions { get; set; }
-        /// <summary>
-        /// Optional. The number of dimensions the resulting output embeddings should have.
-        /// Passing null causes the model to use its default value.
-        /// Returns a 422 error if the model doesn't support the value or parameter.
-        /// </summary>
-        public EmbeddingEncodingFormat? EncodingFormat { get; set; }
-        /// <summary>
-        /// Optional. The type of the input.
-        /// Returns a 422 error if the model doesn't support the value or parameter.
-        /// </summary>
-        public EmbeddingInputType? InputType { get; set; }
-        /// <summary> ID of the specific AI model to use, if more than one model is available on the endpoint. </summary>
-        public string Model { get; set; }
-        /// <summary>
-        /// Additional Properties
-        /// <para>
-        /// To assign an object to the value of this property use <see cref="BinaryData.FromObjectAsJson{T}(T, System.Text.Json.JsonSerializerOptions?)"/>.
-        /// </para>
-        /// <para>
-        /// To assign an already formatted json string to this property use <see cref="BinaryData.FromString(string)"/>.
-        /// </para>
-        /// <para>
-        /// Examples:
-        /// <list type="bullet">
-        /// <item>
-        /// <term>BinaryData.FromObjectAsJson("foo")</term>
-        /// <description>Creates a payload of "foo".</description>
-        /// </item>
-        /// <item>
-        /// <term>BinaryData.FromString("\"foo\"")</term>
-        /// <description>Creates a payload of "foo".</description>
-        /// </item>
-        /// <item>
-        /// <term>BinaryData.FromObjectAsJson(new { key = "value" })</term>
-        /// <description>Creates a payload of { "key": "value" }.</description>
-        /// </item>
-        /// <item>
-        /// <term>BinaryData.FromString("{\"key\": \"value\"}")</term>
-        /// <description>Creates a payload of { "key": "value" }.</description>
-        /// </item>
-        /// </list>
-        /// </para>
-        /// </summary>
-        public IDictionary<string, BinaryData> AdditionalProperties { get; }
-    }
-}
diff --git a/sdk/ai/Azure.AI.Inference/tests/Generated/Samples/Samples_EmbeddingsClient.cs b/sdk/ai/Azure.AI.Inference/tests/Generated/Samples/Samples_EmbeddingsClient.cs
deleted file mode 100644
index a6f43d432014..000000000000
--- a/sdk/ai/Azure.AI.Inference/tests/Generated/Samples/Samples_EmbeddingsClient.cs
+++ /dev/null
@@ -1,126 +0,0 @@
-// Copyright (c) Microsoft Corporation. All rights reserved.
-// Licensed under the MIT License.
-
-// <auto-generated/>
-
-#nullable disable
-
-using System;
-using System.Text.Json;
-using System.Threading.Tasks;
-using Azure.Identity;
-using NUnit.Framework;
-
-namespace Azure.AI.Inference.Samples
-{
-    public partial class Samples_EmbeddingsClient
-    {
-        [Test]
-        [Ignore("Only validating compilation of examples")]
-        public void Example_Client2_GetModelInfo_MaximumSetModelInformation()
-        {
-            Uri endpoint = new Uri("<endpoint>");
-            AzureKeyCredential credential = new AzureKeyCredential("<key>");
-            EmbeddingsClient client = new EmbeddingsClient(endpoint, credential);
-
-            Response response = client.GetModelInfo(null);
-
-            JsonElement result = JsonDocument.Parse(response.ContentStream).RootElement;
-            Console.WriteLine(result.GetProperty("model_name").ToString());
-            Console.WriteLine(result.GetProperty("model_type").ToString());
-            Console.WriteLine(result.GetProperty("model_provider_name").ToString());
-        }
-
-        [Test]
-        [Ignore("Only validating compilation of examples")]
-        public async Task Example_Client2_GetModelInfo_MaximumSetModelInformation_Async()
-        {
-            Uri endpoint = new Uri("<endpoint>");
-            AzureKeyCredential credential = new AzureKeyCredential("<key>");
-            EmbeddingsClient client = new EmbeddingsClient(endpoint, credential);
-
-            Response response = await client.GetModelInfoAsync(null);
-
-            JsonElement result = JsonDocument.Parse(response.ContentStream).RootElement;
-            Console.WriteLine(result.GetProperty("model_name").ToString());
-            Console.WriteLine(result.GetProperty("model_type").ToString());
-            Console.WriteLine(result.GetProperty("model_provider_name").ToString());
-        }
-
-        [Test]
-        [Ignore("Only validating compilation of examples")]
-        public void Example_Client2_GetModelInfo_MaximumSetModelInformation_Convenience()
-        {
-            Uri endpoint = new Uri("<endpoint>");
-            AzureKeyCredential credential = new AzureKeyCredential("<key>");
-            EmbeddingsClient client = new EmbeddingsClient(endpoint, credential);
-
-            Response<ModelInfo> response = client.GetModelInfo();
-        }
-
-        [Test]
-        [Ignore("Only validating compilation of examples")]
-        public async Task Example_Client2_GetModelInfo_MaximumSetModelInformation_Convenience_Async()
-        {
-            Uri endpoint = new Uri("<endpoint>");
-            AzureKeyCredential credential = new AzureKeyCredential("<key>");
-            EmbeddingsClient client = new EmbeddingsClient(endpoint, credential);
-
-            Response<ModelInfo> response = await client.GetModelInfoAsync();
-        }
-
-        [Test]
-        [Ignore("Only validating compilation of examples")]
-        public void Example_Client2_GetModelInfo_MinimumSetModelInformation()
-        {
-            Uri endpoint = new Uri("<endpoint>");
-            AzureKeyCredential credential = new AzureKeyCredential("<key>");
-            EmbeddingsClient client = new EmbeddingsClient(endpoint, credential);
-
-            Response response = client.GetModelInfo(null);
-
-            JsonElement result = JsonDocument.Parse(response.ContentStream).RootElement;
-            Console.WriteLine(result.GetProperty("model_name").ToString());
-            Console.WriteLine(result.GetProperty("model_type").ToString());
-            Console.WriteLine(result.GetProperty("model_provider_name").ToString());
-        }
-
-        [Test]
-        [Ignore("Only validating compilation of examples")]
-        public async Task Example_Client2_GetModelInfo_MinimumSetModelInformation_Async()
-        {
-            Uri endpoint = new Uri("<endpoint>");
-            AzureKeyCredential credential = new AzureKeyCredential("<key>");
-            EmbeddingsClient client = new EmbeddingsClient(endpoint, credential);
-
-            Response response = await client.GetModelInfoAsync(null);
-
-            JsonElement result = JsonDocument.Parse(response.ContentStream).RootElement;
-            Console.WriteLine(result.GetProperty("model_name").ToString());
-            Console.WriteLine(result.GetProperty("model_type").ToString());
-            Console.WriteLine(result.GetProperty("model_provider_name").ToString());
-        }
-
-        [Test]
-        [Ignore("Only validating compilation of examples")]
-        public void Example_Client2_GetModelInfo_MinimumSetModelInformation_Convenience()
-        {
-            Uri endpoint = new Uri("<endpoint>");
-            AzureKeyCredential credential = new AzureKeyCredential("<key>");
-            EmbeddingsClient client = new EmbeddingsClient(endpoint, credential);
-
-            Response<ModelInfo> response = client.GetModelInfo();
-        }
-
-        [Test]
-        [Ignore("Only validating compilation of examples")]
-        public async Task Example_Client2_GetModelInfo_MinimumSetModelInformation_Convenience_Async()
-        {
-            Uri endpoint = new Uri("<endpoint>");
-            AzureKeyCredential credential = new AzureKeyCredential("<key>");
-            EmbeddingsClient client = new EmbeddingsClient(endpoint, credential);
-
-            Response<ModelInfo> response = await client.GetModelInfoAsync();
-        }
-    }
-}
diff --git a/sdk/ai/Azure.AI.Inference/tests/Generated/Samples/Samples_ImageEmbeddingsClient.cs b/sdk/ai/Azure.AI.Inference/tests/Generated/Samples/Samples_ImageEmbeddingsClient.cs
deleted file mode 100644
index 7c068f00b89c..000000000000
--- a/sdk/ai/Azure.AI.Inference/tests/Generated/Samples/Samples_ImageEmbeddingsClient.cs
+++ /dev/null
@@ -1,126 +0,0 @@
-// Copyright (c) Microsoft Corporation. All rights reserved.
-// Licensed under the MIT License.
-
-// <auto-generated/>
-
-#nullable disable
-
-using System;
-using System.Text.Json;
-using System.Threading.Tasks;
-using Azure.Identity;
-using NUnit.Framework;
-
-namespace Azure.AI.Inference.Samples
-{
-    public partial class Samples_ImageEmbeddingsClient
-    {
-        [Test]
-        [Ignore("Only validating compilation of examples")]
-        public void Example_Client3_GetModelInfo_MaximumSetModelInformation()
-        {
-            Uri endpoint = new Uri("<endpoint>");
-            AzureKeyCredential credential = new AzureKeyCredential("<key>");
-            ImageEmbeddingsClient client = new ImageEmbeddingsClient(endpoint, credential);
-
-            Response response = client.GetModelInfo(null);
-
-            JsonElement result = JsonDocument.Parse(response.ContentStream).RootElement;
-            Console.WriteLine(result.GetProperty("model_name").ToString());
-            Console.WriteLine(result.GetProperty("model_type").ToString());
-            Console.WriteLine(result.GetProperty("model_provider_name").ToString());
-        }
-
-        [Test]
-        [Ignore("Only validating compilation of examples")]
-        public async Task Example_Client3_GetModelInfo_MaximumSetModelInformation_Async()
-        {
-            Uri endpoint = new Uri("<endpoint>");
-            AzureKeyCredential credential = new AzureKeyCredential("<key>");
-            ImageEmbeddingsClient client = new ImageEmbeddingsClient(endpoint, credential);
-
-            Response response = await client.GetModelInfoAsync(null);
-
-            JsonElement result = JsonDocument.Parse(response.ContentStream).RootElement;
-            Console.WriteLine(result.GetProperty("model_name").ToString());
-            Console.WriteLine(result.GetProperty("model_type").ToString());
-            Console.WriteLine(result.GetProperty("model_provider_name").ToString());
-        }
-
-        [Test]
-        [Ignore("Only validating compilation of examples")]
-        public void Example_Client3_GetModelInfo_MaximumSetModelInformation_Convenience()
-        {
-            Uri endpoint = new Uri("<endpoint>");
-            AzureKeyCredential credential = new AzureKeyCredential("<key>");
-            ImageEmbeddingsClient client = new ImageEmbeddingsClient(endpoint, credential);
-
-            Response<ModelInfo> response = client.GetModelInfo();
-        }
-
-        [Test]
-        [Ignore("Only validating compilation of examples")]
-        public async Task Example_Client3_GetModelInfo_MaximumSetModelInformation_Convenience_Async()
-        {
-            Uri endpoint = new Uri("<endpoint>");
-            AzureKeyCredential credential = new AzureKeyCredential("<key>");
-            ImageEmbeddingsClient client = new ImageEmbeddingsClient(endpoint, credential);
-
-            Response<ModelInfo> response = await client.GetModelInfoAsync();
-        }
-
-        [Test]
-        [Ignore("Only validating compilation of examples")]
-        public void Example_Client3_GetModelInfo_MinimumSetModelInformation()
-        {
-            Uri endpoint = new Uri("<endpoint>");
-            AzureKeyCredential credential = new AzureKeyCredential("<key>");
-            ImageEmbeddingsClient client = new ImageEmbeddingsClient(endpoint, credential);
-
-            Response response = client.GetModelInfo(null);
-
-            JsonElement result = JsonDocument.Parse(response.ContentStream).RootElement;
-            Console.WriteLine(result.GetProperty("model_name").ToString());
-            Console.WriteLine(result.GetProperty("model_type").ToString());
-            Console.WriteLine(result.GetProperty("model_provider_name").ToString());
-        }
-
-        [Test]
-        [Ignore("Only validating compilation of examples")]
-        public async Task Example_Client3_GetModelInfo_MinimumSetModelInformation_Async()
-        {
-            Uri endpoint = new Uri("<endpoint>");
-            AzureKeyCredential credential = new AzureKeyCredential("<key>");
-            ImageEmbeddingsClient client = new ImageEmbeddingsClient(endpoint, credential);
-
-            Response response = await client.GetModelInfoAsync(null);
-
-            JsonElement result = JsonDocument.Parse(response.ContentStream).RootElement;
-            Console.WriteLine(result.GetProperty("model_name").ToString());
-            Console.WriteLine(result.GetProperty("model_type").ToString());
-            Console.WriteLine(result.GetProperty("model_provider_name").ToString());
-        }
-
-        [Test]
-        [Ignore("Only validating compilation of examples")]
-        public void Example_Client3_GetModelInfo_MinimumSetModelInformation_Convenience()
-        {
-            Uri endpoint = new Uri("<endpoint>");
-            AzureKeyCredential credential = new AzureKeyCredential("<key>");
-            ImageEmbeddingsClient client = new ImageEmbeddingsClient(endpoint, credential);
-
-            Response<ModelInfo> response = client.GetModelInfo();
-        }
-
-        [Test]
-        [Ignore("Only validating compilation of examples")]
-        public async Task Example_Client3_GetModelInfo_MinimumSetModelInformation_Convenience_Async()
-        {
-            Uri endpoint = new Uri("<endpoint>");
-            AzureKeyCredential credential = new AzureKeyCredential("<key>");
-            ImageEmbeddingsClient client = new ImageEmbeddingsClient(endpoint, credential);
-
-            Response<ModelInfo> response = await client.GetModelInfoAsync();
-        }
-    }
-}
diff --git a/sdk/ai/Azure.AI.Inference/tsp-location.yaml b/sdk/ai/Azure.AI.Inference/tsp-location.yaml
index 4ddcd7950ab7..bb2885957e94 100644
--- a/sdk/ai/Azure.AI.Inference/tsp-location.yaml
+++ b/sdk/ai/Azure.AI.Inference/tsp-location.yaml
@@ -1,3 +1,4 @@
 directory: specification/ai/ModelClient
-repo: trangevi/azure-rest-api-specs
-commit: 41bbb0705062205769a3360373705880ee98b6a5
+commit: 8caaac74177821a7cd27722e0cabb6b21b26b14f
+repo: Azure/azure-rest-api-specs
+additionalDirectories: