Tweaks to main M.E.AI landing doc (#46276)

Author: stephentoub

docs/ai/microsoft-extensions-ai.md

@@ -84,11 +84,11 @@ Helpers like <xref:Microsoft.Extensions.AI.ChatResponseExtensions.AddMessages*>
 
 #### Tool calling
 
-Some models and services support _tool calling_. To gather additional information, you can configure the <xref:Microsoft.Extensions.AI.ChatOptions> with information about tools (usually .NET methods) that the model can request the client to invoke. Instead of sending a final response, the model requests a function invocation with specific arguments. The client then invokes the function and sends the results back to the model with the conversation history. The `Microsoft.Extensions.AI` library includes abstractions for various message content types, including function call requests and results. While `IChatClient` consumers can interact with this content directly, `Microsoft.Extensions.AI` automates these interactions pro. It provides the following types:
+Some models and services support _tool calling_. To gather additional information, you can configure the <xref:Microsoft.Extensions.AI.ChatOptions> with information about tools (usually .NET methods) that the model can request the client to invoke. Instead of sending a final response, the model requests a function invocation with specific arguments. The client then invokes the function and sends the results back to the model with the conversation history. The `Microsoft.Extensions.AI.Abstractions` library includes abstractions for various message content types, including function call requests and results. While `IChatClient` consumers can interact with this content directly, `Microsoft.Extensions.AI` provides helpers that can enable automatically invoking the tools in response to corresponding requests. The `Microsoft.Extensions.AI.Abstractions` and `Microsoft.Extensions.AI` libraries provide the following types:
 
 - <xref:Microsoft.Extensions.AI.AIFunction>: Represents a function that can be described to an AI model and invoked.
 - <xref:Microsoft.Extensions.AI.AIFunctionFactory>: Provides factory methods for creating `AIFunction` instances that represent .NET methods.
-- <xref:Microsoft.Extensions.AI.FunctionInvokingChatClient>: Wraps an `IChatClient` to add automatic function-invocation capabilities.
+- <xref:Microsoft.Extensions.AI.FunctionInvokingChatClient>: Wraps an `IChatClient` as another `IChatClient` that adds automatic function-invocation capabilities.
 
 The following example demonstrates a random function invocation (this example depends on the [📦 Microsoft.Extensions.AI.Ollama](https://www.nuget.org/packages/Microsoft.Extensions.AI.Ollama) NuGet package):
 
@@ -121,7 +121,7 @@ Alternatively, the <xref:Microsoft.Extensions.AI.LoggingChatClient> and correspo
 
 #### Provide options
 
-Every call to <xref:Microsoft.Extensions.AI.IChatClient.GetResponseAsync*> or <xref:Microsoft.Extensions.AI.IChatClient.GetStreamingResponseAsync*> can optionally supply a <xref:Microsoft.Extensions.AI.ChatOptions> instance containing additional parameters for the operation. The most common parameters among AI models and services show up as strongly typed properties on the type, such as <xref:Microsoft.Extensions.AI.ChatOptions.Temperature?displayProperty=nameWithType>. Other parameters can be supplied by name in a weakly typed manner, via the <xref:Microsoft.Extensions.AI.ChatOptions.AdditionalProperties?displayProperty=nameWithType> dictionary.
+Every call to <xref:Microsoft.Extensions.AI.IChatClient.GetResponseAsync*> or <xref:Microsoft.Extensions.AI.IChatClient.GetStreamingResponseAsync*> can optionally supply a <xref:Microsoft.Extensions.AI.ChatOptions> instance containing additional parameters for the operation. The most common parameters among AI models and services show up as strongly typed properties on the type, such as <xref:Microsoft.Extensions.AI.ChatOptions.Temperature?displayProperty=nameWithType>. Other parameters can be supplied by name in a weakly typed manner, via the <xref:Microsoft.Extensions.AI.ChatOptions.AdditionalProperties?displayProperty=nameWithType> dictionary, or via an options instance that the underlying provider understands, via the <xref:Microsoft.Extensions.AI.ChatOptions.RawRepresentationFactory?displayProperty=nameWithType> property.
 
 You can also specify options when building an `IChatClient` with the fluent <xref:Microsoft.Extensions.AI.ChatClientBuilder> API by chaining a call to the <xref:Microsoft.Extensions.AI.ConfigureOptionsChatClientBuilderExtensions.ConfigureOptions(Microsoft.Extensions.AI.ChatClientBuilder,System.Action{Microsoft.Extensions.AI.ChatOptions})> extension method. This delegating client wraps another client and invokes the supplied delegate to populate a `ChatOptions` instance for every call. For example, to ensure that the <xref:Microsoft.Extensions.AI.ChatOptions.ModelId?displayProperty=nameWithType> property defaults to a particular model name, you can use code like the following:
 
@@ -185,7 +185,7 @@ For stateful services, you might already know the identifier used for the releva
 
 :::code language="csharp" source="snippets/microsoft-extensions-ai/ConsoleAI.StatelessStateful/Program.cs" id="Snippet2":::
 
-Some services might support automatically creating a thread ID for a request that doesn't have one. In such cases, you can transfer the <xref:Microsoft.Extensions.AI.ChatResponse.ConversationId?displayProperty=nameWithType> over to the `ChatOptions.ConversationId` for subsequent requests. For example:
+Some services might support automatically creating a conversation ID for a request that doesn't have one, or creating a new conversation ID that represents the current state of the conversation after incorporating the last round of messages. In such cases, you can transfer the <xref:Microsoft.Extensions.AI.ChatResponse.ConversationId?displayProperty=nameWithType> over to the `ChatOptions.ConversationId` for subsequent requests. For example:
 
 :::code language="csharp" source="snippets/microsoft-extensions-ai/ConsoleAI.StatelessStateful/Program.cs" id="Snippet3":::
 
@@ -251,7 +251,7 @@ In this way, the `RateLimitingEmbeddingGenerator` can be composed with other `IE
 You can start building with `Microsoft.Extensions.AI` in the following ways:
 
 - **Library developers**: If you own libraries that provide clients for AI services, consider implementing the interfaces in your libraries. This allows users to easily integrate your NuGet package via the abstractions.
-- **Service consumers**: If you're developing libraries that consume AI services, use the abstractions instead of hardcoding to a specific AI service. This approach gives your consumers the flexibility to choose their preferred service.
+- **Service consumers**: If you're developing libraries that consume AI services, use the abstractions instead of hardcoding to a specific AI service. This approach gives your consumers the flexibility to choose their preferred provider.
 - **Application developers**: Use the abstractions to simplify integration into your apps. This enables portability across models and services, facilitates testing and mocking, leverages middleware provided by the ecosystem, and maintains a consistent API throughout your app, even if you use different services in different parts of your application.
 - **Ecosystem contributors**: If you're interested in contributing to the ecosystem, consider writing custom middleware components.