Add samples. Regenerate apiview

Signed-off-by: Travis Angevine <[email protected]>

sdk/ai/Azure.AI.Inference/samples/Sample1_ChatCompletions.md

@@ -14,7 +14,7 @@ Set these two environment variables before running the sample:
 var endpoint = new Uri(System.Environment.GetEnvironmentVariable("AZURE_AI_CHAT_ENDPOINT"));
 var credential = new AzureKeyCredential(System.Environment.GetEnvironmentVariable("AZURE_AI_CHAT_KEY"));
 
-var client = new ChatCompletionsClient(endpoint, credential, new ChatCompletionsClientOptions());
+var client = new ChatCompletionsClient(endpoint, credential, new AzureAIInferenceClientOptions());
 
 var requestOptions = new ChatCompletionsOptions()
 {
@@ -35,7 +35,7 @@ An `async` option is also available.
 var endpoint = new Uri(System.Environment.GetEnvironmentVariable("AZURE_AI_CHAT_ENDPOINT"));
 var credential = new AzureKeyCredential(System.Environment.GetEnvironmentVariable("AZURE_AI_CHAT_KEY"));
 
-var client = new ChatCompletionsClient(endpoint, credential, new ChatCompletionsClientOptions());
+var client = new ChatCompletionsClient(endpoint, credential, new AzureAIInferenceClientOptions());
 
 var requestOptions = new ChatCompletionsOptions()
 {

sdk/ai/Azure.AI.Inference/samples/Sample2_ChatCompletionsWithAoai.md

@@ -49,7 +49,7 @@ var key = System.Environment.GetEnvironmentVariable("AZURE_OPENAI_CHAT_KEY");
 // the credential object is still required. So create with a dummy value.
 var credential = new AzureKeyCredential("foo");
 
-ChatCompletionsClientOptions clientOptions = new ChatCompletionsClientOptions();
+AzureAIInferenceClientOptions clientOptions = new AzureAIInferenceClientOptions();
 clientOptions.AddPolicy(new AddAoaiAuthHeaderPolicy(key), HttpPipelinePosition.PerCall);
 
 var client = new ChatCompletionsClient(endpoint, credential, clientOptions);
@@ -61,7 +61,7 @@ Alternatively, you can use EntraId to authenticate. This does not require the he
 var endpoint = new Uri(System.Environment.GetEnvironmentVariable("AZURE_OPENAI_CHAT_ENDPOINT"));
 var credential = new DefaultAzureCredential(includeInteractiveCredentials: true);
 
-ChatCompletionsClientOptions clientOptions = new ChatCompletionsClientOptions();
+AzureAIInferenceClientOptions clientOptions = new AzureAIInferenceClientOptions();
 
 BearerTokenAuthenticationPolicy tokenPolicy = new BearerTokenAuthenticationPolicy(credential, new string[] { "https://cognitiveservices.azure.com/.default" });
 clientOptions.AddPolicy(tokenPolicy, HttpPipelinePosition.PerRetry);

sdk/ai/Azure.AI.Inference/samples/Sample3_ChatCompletionsStreaming.md

@@ -14,7 +14,7 @@ Set these two environment variables before running the sample:
 var endpoint = new Uri(System.Environment.GetEnvironmentVariable("AZURE_AI_CHAT_ENDPOINT"));
 var credential = new AzureKeyCredential(System.Environment.GetEnvironmentVariable("AZURE_AI_CHAT_KEY"));
 
-var client = new ChatCompletionsClient(endpoint, credential, new ChatCompletionsClientOptions());
+var client = new ChatCompletionsClient(endpoint, credential, new AzureAIInferenceClientOptions());
 
 var requestOptions = new ChatCompletionsOptions()
 {
@@ -48,7 +48,7 @@ An `async` option is also available for the initial streaming call.
 var endpoint = new Uri(System.Environment.GetEnvironmentVariable("AZURE_AI_CHAT_ENDPOINT"));
 var credential = new AzureKeyCredential(System.Environment.GetEnvironmentVariable("AZURE_AI_CHAT_KEY"));
 
-var client = new ChatCompletionsClient(endpoint, credential, new ChatCompletionsClientOptions());
+var client = new ChatCompletionsClient(endpoint, credential, new AzureAIInferenceClientOptions());
 
 var requestOptions = new ChatCompletionsOptions()
 {

sdk/ai/Azure.AI.Inference/samples/Sample4_ChatCompletionsWithHistory.md

@@ -14,7 +14,7 @@ Set these two environment variables before running the sample:
 var endpoint = new Uri(System.Environment.GetEnvironmentVariable("AZURE_AI_CHAT_ENDPOINT"));
 var credential = new AzureKeyCredential(System.Environment.GetEnvironmentVariable("AZURE_AI_CHAT_KEY"));
 
-var client = new ChatCompletionsClient(endpoint, credential, new ChatCompletionsClientOptions());
+var client = new ChatCompletionsClient(endpoint, credential, new AzureAIInferenceClientOptions());
 var messages = new List<ChatRequestMessage>()
 {
     new ChatRequestSystemMessage("You are an AI assistant that helps people find information. Your replies are short, no more than two sentences."),
@@ -40,7 +40,7 @@ An `async` option is also available.
 var endpoint = new Uri(System.Environment.GetEnvironmentVariable("AZURE_AI_CHAT_ENDPOINT"));
 var credential = new AzureKeyCredential(System.Environment.GetEnvironmentVariable("AZURE_AI_CHAT_KEY"));
 
-var client = new ChatCompletionsClient(endpoint, credential, new ChatCompletionsClientOptions());
+var client = new ChatCompletionsClient(endpoint, credential, new AzureAIInferenceClientOptions());
 var messages = new List<ChatRequestMessage>()
 {
     new ChatRequestSystemMessage("You are an AI assistant that helps people find information. Your replies are short, no more than two sentences."),

sdk/ai/Azure.AI.Inference/samples/Sample5_ChatCompletionsWithImageUrl.md

@@ -16,7 +16,7 @@ Set these two environment variables before running the sample:
 var endpoint = new Uri(System.Environment.GetEnvironmentVariable("AZURE_AI_CHAT_ENDPOINT"));
 var credential = new AzureKeyCredential(System.Environment.GetEnvironmentVariable("AZURE_AI_CHAT_KEY"));
 
-var client = new ChatCompletionsClient(endpoint, credential, new ChatCompletionsClientOptions());
+var client = new ChatCompletionsClient(endpoint, credential, new AzureAIInferenceClientOptions());
 
 ChatMessageImageContentItem imageContentItem =
     new ChatMessageImageContentItem(
@@ -45,7 +45,7 @@ An `async` option is also available.
 var endpoint = new Uri(System.Environment.GetEnvironmentVariable("AZURE_AI_CHAT_ENDPOINT"));
 var credential = new AzureKeyCredential(System.Environment.GetEnvironmentVariable("AZURE_AI_CHAT_KEY"));
 
-var client = new ChatCompletionsClient(endpoint, credential, new ChatCompletionsClientOptions());
+var client = new ChatCompletionsClient(endpoint, credential, new AzureAIInferenceClientOptions());
 
 ChatMessageImageContentItem imageContentItem =
     new ChatMessageImageContentItem(

sdk/ai/Azure.AI.Inference/samples/Sample6_ChatCompletionsWithAdditionalProperties.md

@@ -14,7 +14,7 @@ Set these two environment variables before running the sample:
 var endpoint = new Uri(System.Environment.GetEnvironmentVariable("AZURE_AI_CHAT_ENDPOINT"));
 var credential = new AzureKeyCredential(System.Environment.GetEnvironmentVariable("AZURE_AI_CHAT_KEY"));
 
-var client = new ChatCompletionsClient(endpoint, credential, new ChatCompletionsClientOptions());
+var client = new ChatCompletionsClient(endpoint, credential, new AzureAIInferenceClientOptions());
 
 var requestOptions = new ChatCompletionsOptions()
 {
@@ -41,7 +41,7 @@ An `async` option is also available.
 var endpoint = new Uri(System.Environment.GetEnvironmentVariable("AZURE_AI_CHAT_ENDPOINT"));
 var credential = new AzureKeyCredential(System.Environment.GetEnvironmentVariable("AZURE_AI_CHAT_KEY"));
 
-var client = new ChatCompletionsClient(endpoint, credential, new ChatCompletionsClientOptions());
+var client = new ChatCompletionsClient(endpoint, credential, new AzureAIInferenceClientOptions());
 
 var requestOptions = new ChatCompletionsOptions()
 {

sdk/ai/Azure.AI.Inference/samples/Sample7_ChatCompletionsWithTools.md

@@ -14,7 +14,7 @@ Set these two environment variables before running the sample:
 var endpoint = new Uri(System.Environment.GetEnvironmentVariable("AZURE_AI_CHAT_ENDPOINT"));
 var credential = new AzureKeyCredential(System.Environment.GetEnvironmentVariable("AZURE_AI_CHAT_KEY"));
 
-var client = new ChatCompletionsClient(endpoint, credential, new ChatCompletionsClientOptions());
+var client = new ChatCompletionsClient(endpoint, credential, new AzureAIInferenceClientOptions());
 
 FunctionDefinition futureTemperatureFunction = new FunctionDefinition("get_future_temperature")
 {
@@ -39,7 +39,7 @@ FunctionDefinition futureTemperatureFunction = new FunctionDefinition("get_futur
     },
     new JsonSerializerOptions() { PropertyNamingPolicy = JsonNamingPolicy.CamelCase })
 };
-ChatCompletionsFunctionToolDefinition functionToolDef = new ChatCompletionsFunctionToolDefinition(futureTemperatureFunction);
+ChatCompletionsToolDefinition functionToolDef = new ChatCompletionsToolDefinition(futureTemperatureFunction);
 
 var requestOptions = new ChatCompletionsOptions()
 {
@@ -55,7 +55,7 @@ Response<ChatCompletions> response = client.Complete(requestOptions);
 System.Console.WriteLine(response.Value.Choices[0].Message.Content);
 
 ChatResponseMessage responseMessage = response.Value.Choices[0].Message;
-ChatCompletionsFunctionToolCall functionToolCall = responseMessage.ToolCalls[0] as ChatCompletionsFunctionToolCall;
+ChatCompletionsToolCall functionToolCall = responseMessage.ToolCalls[0] as ChatCompletionsToolCall;
 
 ChatCompletionsOptions followupOptions = new()
 {
@@ -86,7 +86,7 @@ An `async` option is also available.
 var endpoint = new Uri(System.Environment.GetEnvironmentVariable("AZURE_AI_CHAT_ENDPOINT"));
 var credential = new AzureKeyCredential(System.Environment.GetEnvironmentVariable("AZURE_AI_CHAT_KEY"));
 
-var client = new ChatCompletionsClient(endpoint, credential, new ChatCompletionsClientOptions());
+var client = new ChatCompletionsClient(endpoint, credential, new AzureAIInferenceClientOptions());
 
 FunctionDefinition futureTemperatureFunction = new FunctionDefinition("get_future_temperature")
 {
@@ -111,7 +111,7 @@ FunctionDefinition futureTemperatureFunction = new FunctionDefinition("get_futur
     },
     new JsonSerializerOptions() { PropertyNamingPolicy = JsonNamingPolicy.CamelCase })
 };
-ChatCompletionsFunctionToolDefinition functionToolDef = new ChatCompletionsFunctionToolDefinition(futureTemperatureFunction);
+ChatCompletionsToolDefinition functionToolDef = new ChatCompletionsToolDefinition(futureTemperatureFunction);
 
 var requestOptions = new ChatCompletionsOptions()
 {
@@ -127,7 +127,7 @@ Response<ChatCompletions> response = await client.CompleteAsync(requestOptions);
 System.Console.WriteLine(response.Value.Choices[0].Message.Content);
 
 ChatResponseMessage responseMessage = response.Value.Choices[0].Message;
-ChatCompletionsFunctionToolCall functionToolCall = responseMessage.ToolCalls[0] as ChatCompletionsFunctionToolCall;
+ChatCompletionsToolCall functionToolCall = responseMessage.ToolCalls[0] as ChatCompletionsToolCall;
 
 ChatCompletionsOptions followupOptions = new()
 {

sdk/ai/Azure.AI.Inference/samples/Sample8_Embeddings.md

@@ -0,0 +1,68 @@
+# Simple Embeddings
+
+This sample demonstrates how to get text embeddings for a list of sentences. Here we use the service default of returning embeddings as a list of floating point values.
+
+This sample assumes the AI model is hosted on a Serverless API or Managed Compute endpoint. For GitHub Models or Azure OpenAI endpoints, the client constructor needs to be modified. See package documentation for details.
+
+## Usage
+
+Set these two environment variables before running the sample:
+
+1. AZURE_AI_EMBEDDINGS_ENDPOINT - Your endpoint URL, in the form `https://your-deployment-name.your-azure-region.inference.ai.azure.com` where `your-deployment-name` is your unique AI Model deployment name, and `your-azure-region` is the Azure region where your model is deployed.
+
+2. AZURE_AI_EMBEDDINGS_KEY - Your model key (a 32-character string). Keep it secret.
+
+```C# Snippet:Azure_AI_Inference_BasicEmbedding
+var endpoint = new Uri(System.Environment.GetEnvironmentVariable("AZURE_AI_EMBEDDINGS_ENDPOINT"));
+var credential = new AzureKeyCredential(System.Environment.GetEnvironmentVariable("AZURE_AI_EMBEDDINGS_KEY"));
+
+var client = new EmbeddingsClient(endpoint, credential, new AzureAIInferenceClientOptions());
+
+var input = new List<string> { "King", "Queen", "Jack", "Page" };
+var requestOptions = new EmbeddingsOptions(input);
+
+Response<EmbeddingsResult> response = client.Embed(requestOptions);
+foreach (EmbeddingItem item in response.Value.Data)
+{
+    List<float> embedding = item.Embedding.ToObjectFromJson<List<float>>();
+    Console.WriteLine($"Index: {item.Index}, Embedding: <{string.Join(", ", embedding)}>");
+}
+```
+
+An `async` option is also available.
+
+```C# Snippet:Azure_AI_Inference_BasicEmbeddingAsync
+var endpoint = new Uri(System.Environment.GetEnvironmentVariable("AZURE_AI_EMBEDDINGS_ENDPOINT"));
+var credential = new AzureKeyCredential(System.Environment.GetEnvironmentVariable("AZURE_AI_EMBEDDINGS_KEY"));
+
+var client = new EmbeddingsClient(endpoint, credential, new AzureAIInferenceClientOptions());
+
+var input = new List<string> { "King", "Queen", "Jack", "Page" };
+var requestOptions = new EmbeddingsOptions(input);
+
+Response<EmbeddingsResult> response = await client.EmbedAsync(requestOptions);
+foreach (EmbeddingItem item in response.Value.Data)
+{
+    List<float> embedding = item.Embedding.ToObjectFromJson<List<float>>();
+    Console.WriteLine($"Index: {item.Index}, Embedding: <{string.Join(", ", embedding)}>");
+}
+```
+
+### Alternative Response Type
+
+It is also possible to request embeddings as base64 encoded strings, instead of the service default of lists of floats.
+
+```C# Snippet:Azure_AI_Inference_Base64Embedding
+var input = new List<string> { "King", "Queen", "Jack", "Page" };
+var requestOptions = new EmbeddingsOptions(input)
+{
+    EncodingFormat = EmbeddingEncodingFormat.Base64,
+};
+
+Response<EmbeddingsResult> response = client.Embed(requestOptions);
+foreach (EmbeddingItem item in response.Value.Data)
+{
+    string embedding = item.Embedding.ToObjectFromJson<string>();
+    Console.WriteLine($"Index: {item.Index}, Embedding: {embedding}");
+}
+```

sdk/ai/Azure.AI.Inference/samples/Sample9_EmbeddingsWithAoai.md

@@ -0,0 +1,117 @@
+# Simple Embeddings Using Azure OpenAI
+
+This sample demonstrates how to get text embeddings for a list of sentences using a synchronous client, with an Azure OpenAI (AOAI) endpoint. Two types of authentications are shown: key authentication and Entra ID authentication.
+
+## Usage
+
+Set these two environment variables before running the sample:
+
+1. AZURE_OPENAI_EMBEDDINGS_ENDPOINT - Your endpoint URL, in the form `https://your-deployment-name.your-azure-region.inference.ai.azure.com` where `your-deployment-name` is your unique AI Model deployment name, and `your-azure-region` is the Azure region where your model is deployed.
+
+2. AZURE_OPENAI_EMBEDDINGS_KEY - Your model key (a 32-character string). Keep it secret.
+
+In order to target AOAI, the auth key must currently be provided as a separate header. This can be done by creating a `HttpPipelinePolicy` like below:
+
+```C# Snippet:Azure_AI_Inference_AoaiAuthHeaderPolicy
+private class AddAoaiAuthHeaderPolicy : HttpPipelinePolicy
+{
+    public string AoaiKey { get; }
+
+    public AddAoaiAuthHeaderPolicy(string key)
+    {
+        AoaiKey = key;
+    }
+
+    public override void Process(HttpMessage message, ReadOnlyMemory<HttpPipelinePolicy> pipeline)
+    {
+        // Add your desired header name and value
+        message.Request.Headers.Add("api-key", AoaiKey);
+
+        ProcessNext(message, pipeline);
+    }
+
+    public override ValueTask ProcessAsync(HttpMessage message, ReadOnlyMemory<HttpPipelinePolicy> pipeline)
+    {
+        // Add your desired header name and value
+        message.Request.Headers.Add("api-key", AoaiKey);
+
+        return ProcessNextAsync(message, pipeline);
+    }
+}
+```
+
+The policy can then be added to the `AzureAIInferenceClientOptions` object, to configure the client to add the header at runtime.
+
+```C# Snippet:Azure_AI_Inference_BasicEmbeddingAoaiScenarioClientCreate
+var endpoint = new Uri(System.Environment.GetEnvironmentVariable("AZURE_OPENAI_EMBEDDINGS_ENDPOINT"));
+var key = System.Environment.GetEnvironmentVariable("AZURE_OPENAI_EMBEDDINGS_KEY");
+
+// For AOAI, currently the key is passed via a different header not directly handled by the client, however
+// the credential object is still required. So create with a dummy value.
+var credential = new AzureKeyCredential("foo");
+
+AzureAIInferenceClientOptions clientOptions = new AzureAIInferenceClientOptions();
+clientOptions.AddPolicy(new AddAoaiAuthHeaderPolicy(key), HttpPipelinePosition.PerCall);
+
+var client = new EmbeddingsClient(endpoint, credential, clientOptions);
+```
+
+Alternatively, you can use EntraId to authenticate. This does not require the header policy, but it does currently require a separate built-in policy, `BearerTokenAuthenticationPolicy`, to apply the correct token scope.
+
+```C# Snippet:Azure_AI_Inference_EmbeddingWithEntraIdClientCreate
+var endpoint = new Uri(System.Environment.GetEnvironmentVariable("AZURE_OPENAI_EMBEDDINGS_ENDPOINT"));
+var credential = new DefaultAzureCredential(includeInteractiveCredentials: true);
+AzureAIInferenceClientOptions clientOptions = new AzureAIInferenceClientOptions();
+
+BearerTokenAuthenticationPolicy tokenPolicy = new BearerTokenAuthenticationPolicy(credential, new string[] { "https://cognitiveservices.azure.com/.default" });
+clientOptions.AddPolicy(tokenPolicy, HttpPipelinePosition.PerRetry);
+
+var client = new EmbeddingsClient(endpoint, credential, clientOptions);
+```
+
+After the client is created, you can make completion requests with it as shown
+
+```C# Snippet:Azure_AI_Inference_BasicEmbeddingAoai
+var input = new List<string> { "King", "Queen", "Jack", "Page" };
+var requestOptions = new EmbeddingsOptions(input);
+
+Response<EmbeddingsResult> response = client.Embed(requestOptions);
+foreach (EmbeddingItem item in response.Value.Data)
+{
+    List<float> embedding = item.Embedding.ToObjectFromJson<List<float>>();
+    Console.WriteLine($"Index: {item.Index}, Embedding: <{string.Join(", ", embedding)}>");
+}
+```
+
+An `async` option is also available.
+
+```C# Snippet:Azure_AI_Inference_BasicEmbeddingAoaiAsync
+var input = new List<string> { "King", "Queen", "Jack", "Page" };
+var requestOptions = new EmbeddingsOptions(input);
+
+Response<EmbeddingsResult> response = await client.EmbedAsync(requestOptions);
+foreach (EmbeddingItem item in response.Value.Data)
+{
+    List<float> embedding = item.Embedding.ToObjectFromJson<List<float>>();
+    Console.WriteLine($"Index: {item.Index}, Embedding: <{string.Join(", ", embedding)}>");
+}
+```
+
+### Alternative Response Type
+
+It is also possible to request embeddings as base64 encoded strings, instead of the service default of lists of floats.
+
+```C# Snippet:Azure_AI_Inference_Base64Embedding
+var input = new List<string> { "King", "Queen", "Jack", "Page" };
+var requestOptions = new EmbeddingsOptions(input)
+{
+    EncodingFormat = EmbeddingEncodingFormat.Base64,
+};
+
+Response<EmbeddingsResult> response = client.Embed(requestOptions);
+foreach (EmbeddingItem item in response.Value.Data)
+{
+    string embedding = item.Embedding.ToObjectFromJson<string>();
+    Console.WriteLine($"Index: {item.Index}, Embedding: {embedding}");
+}
+```

sdk/ai/Azure.AI.Inference/tests/EmbeddingClientTests.cs

@@ -3,20 +3,10 @@
 
 using System;
 using System.Collections.Generic;
-using System.Diagnostics.Tracing;
-using System.IO;
-using System.Linq;
-using System.Text;
-using System.Text.Json;
 using System.Threading.Tasks;
 using Azure.Core;
-using Azure.Core.Diagnostics;
-using Azure.Core.Pipeline;
 using Azure.Core.TestFramework;
-using Azure.Identity;
-using Newtonsoft.Json;
 using NUnit.Framework;
-using File = System.IO.File;
 
 namespace Azure.AI.Inference.Tests
 {
@@ -83,7 +73,7 @@ public async Task TestEmbedWithBase64()
             Assert.That(response.Value.Usage.TotalTokens, Is.GreaterThan(0));
         }
 
-            #region Helpers
+        #region Helpers
         private EmbeddingsClient CreateClient(Uri endpoint, AzureKeyCredential credential, AzureAIInferenceClientOptions clientOptions)
         {
             return InstrumentClient(new EmbeddingsClient(endpoint, credential, InstrumentClientOptions(clientOptions)));

sdk/ai/Azure.AI.Inference/tests/InferenceClientTestEnvironment.cs

@@ -14,7 +14,9 @@ public class InferenceClientTestEnvironment : TestEnvironment
         public string GithubEndpoint => GetRecordedVariable("AZUREAI_GITHUB_URL");
         public string GithubToken => GetRecordedVariable("AZUREAI_GITHUB_TOKEN", options => options.IsSecret());
         public string AoaiEndpoint => GetRecordedVariable("AOAI_CHAT_COMPLETIONS_ENDPOINT");
-        public string AoaiKey => GetRecordedVariable("AOAI_CHAT_COMPLETIONS_KEY");
+        public string AoaiKey => GetRecordedVariable("AOAI_CHAT_COMPLETIONS_KEY", options => options.IsSecret());
+        public string AoaiEmbeddingsEndpoint => GetRecordedVariable("AOAI_EMBEDDINGS_ENDPOINT");
+        public string AoaiEmbeddingsKey => GetRecordedVariable("AOAI_EMBEDDINGS_KEY", options => options.IsSecret());
         public string TestImageJpgInputPath => GetRecordedVariable("AZUREAI_TEST_IMAGE_JPG_INPUT_PATH");
 
         // Add other client paramters here as above.