Merge branch 'v1.15' into feat-stable-wf-scheduler-updates

daprdocs/content/en/developing-applications/building-blocks/conversation/howto-conversation-layer.md

@@ -34,6 +34,28 @@ spec:
   version: v1
 ```
 
+### Use the OpenAI component
+
+To interface with a real LLM, use one of the other [supported conversation components]({{< ref "supported-conversation" >}}), including OpenAI, Hugging Face, Anthropic, DeepSeek, and more.
+
+For example, to swap out the `echo` mock component with an `OpenAI` component, replace the `conversation.yaml` file with the following. You'll need to copy your API key into the component file.
+
+```
+apiVersion: dapr.io/v1alpha1
+kind: Component
+metadata:
+  name: openai
+spec:
+  type: conversation.openai
+  metadata:
+  - name: key
+    value: <REPLACE_WITH_YOUR_KEY>
+  - name: model
+    value: gpt-4-turbo
+  - name: cacheTTL
+    value: 10m
+```
+
 ## Connect the conversation client
 
 The following examples use an HTTP client to send a POST request to Dapr's sidecar HTTP endpoint. You can also use [the Dapr SDK client instead]({{< ref "#related-links" >}}).

daprdocs/content/en/getting-started/quickstarts/conversation-quickstart.md

@@ -0,0 +1,412 @@
+---
+type: docs
+title: "Quickstart: Conversation"
+linkTitle: Conversation
+weight: 90
+description: Get started with the Dapr conversation building block
+---
+
+{{% alert title="Alpha" color="warning" %}}
+The conversation building block is currently in **alpha**. 
+{{% /alert %}}
+
+Let's take a look at how the [Dapr conversation building block]({{< ref conversation-overview.md >}}) makes interacting with Large Language Models (LLMs) easier. In this quickstart, you use the echo component to communicate with the mock LLM and ask it for a poem about Dapr. 
+
+You can try out this conversation quickstart by either:
+
+- [Running the application in this sample with the Multi-App Run template file]({{< ref "#run-the-app-with-the-template-file" >}}), or
+- [Running the application without the template]({{< ref "#run-the-app-without-the-template" >}})
+
+
+## Run the app with the template file
+
+{{< tabs ".NET" Go >}}
+
+ <!-- .NET -->
+{{% codetab %}}
+
+
+### Step 1: Pre-requisites
+
+For this example, you will need:
+
+- [Dapr CLI and initialized environment](https://docs.dapr.io/getting-started).
+- [.NET 8 SDK+ installed](https://dotnet.microsoft.com/download).
+<!-- IGNORE_LINKS -->
+- [Docker Desktop](https://www.docker.com/products/docker-desktop)
+<!-- END_IGNORE -->
+
+### Step 2: Set up the environment
+
+Clone the [sample provided in the Quickstarts repo](https://github.com/dapr/quickstarts/tree/master/conversation).
+
+```bash
+git clone https://github.com/dapr/quickstarts.git
+```
+
+From the root of the Quickstarts directory, navigate into the conversation directory:
+
+```bash
+cd conversation/csharp/sdk
+```
+
+### Step 3: Launch the conversation service
+
+Start the conversation service with the following command:
+
+```bash
+dapr run -f .
+```
+
+**Expected output**
+
+```
+== APP - conversation == Input sent: What is dapr?
+== APP - conversation == Output response: What is dapr?
+```
+
+### What happened?
+
+When you ran `dapr init` during Dapr install, the [`dapr.yaml` Multi-App Run template file]({{< ref "#dapryaml-multi-app-run-template-file" >}}) was generated in the `.dapr/components` directory.
+
+Running `dapr run -f .` in this Quickstart started the [conversation Program.cs]({{< ref "#programcs-conversation-app" >}}).
+
+#### `dapr.yaml` Multi-App Run template file
+
+Running the [Multi-App Run template file]({{< ref multi-app-dapr-run >}}) with `dapr run -f .` starts all applications in your project. This Quickstart has only one application, so the `dapr.yaml` file contains the following: 
+
+```yml
+version: 1
+common:
+  resourcesPath: ../../components/
+apps:
+  - appDirPath: ./conversation/
+    appID: conversation
+    daprHTTPPort: 3500
+    command: ["dotnet", "run"]
+```
+
+#### Echo mock LLM component
+
+In [`conversation/components`](https://github.com/dapr/quickstarts/tree/master/conversation/components), the [`conversation.yaml` file](https://github.com/dapr/quickstarts/tree/master/conversation/components/conversation.yml) configures the echo mock LLM component. 
+
+```yml
+apiVersion: dapr.io/v1alpha1
+kind: Component
+metadata:
+  name: echo
+spec:
+  type: conversation.echo
+  version: v1
+```
+
+To interface with a real LLM, swap out the mock component with one of [the supported conversation components]({{< ref "supported-conversation" >}}). For example, to use an OpenAI component, see the [example in the conversation how-to guide]({{< ref "howto-conversation-layer.md#use-the-openai-component" >}})
+
+#### `Program.cs` conversation app
+
+In the application code:
+- The app sends an input "What is dapr?" to the echo mock LLM component.
+- The mock LLM echoes "What is dapr?". 
+
+```csharp
+using Dapr.AI.Conversation;
+using Dapr.AI.Conversation.Extensions;
+
+class Program
+{
+  private const string ConversationComponentName = "echo";
+
+  static async Task Main(string[] args)
+  {
+    const string prompt = "What is dapr?";
+
+    var builder = WebApplication.CreateBuilder(args);
+    builder.Services.AddDaprConversationClient();
+    var app = builder.Build();
+
+    //Instantiate Dapr Conversation Client
+    var conversationClient = app.Services.GetRequiredService<DaprConversationClient>();
+
+    try
+    {
+      // Send a request to the echo mock LLM component
+      var response = await conversationClient.ConverseAsync(ConversationComponentName, [new(prompt, DaprConversationRole.Generic)]);
+      Console.WriteLine("Input sent: " + prompt);
+
+      if (response != null)
+      {
+        Console.Write("Output response:");
+        foreach (var resp in response.Outputs)
+        {
+          Console.WriteLine($" {resp.Result}");
+        }
+      }
+    }
+    catch (Exception ex)
+    {
+      Console.WriteLine("Error: " + ex.Message);
+    }
+  }
+}
+```
+
+{{% /codetab %}}
+
+ <!-- Go -->
+{{% codetab %}}
+
+
+### Step 1: Pre-requisites
+
+For this example, you will need:
+
+- [Dapr CLI and initialized environment](https://docs.dapr.io/getting-started).
+- [Latest version of Go](https://go.dev/dl/).
+<!-- IGNORE_LINKS -->
+- [Docker Desktop](https://www.docker.com/products/docker-desktop)
+<!-- END_IGNORE -->
+
+### Step 2: Set up the environment
+
+Clone the [sample provided in the Quickstarts repo](https://github.com/dapr/quickstarts/tree/master/conversation).
+
+```bash
+git clone https://github.com/dapr/quickstarts.git
+```
+
+From the root of the Quickstarts directory, navigate into the conversation directory:
+
+```bash
+cd conversation/go/sdk
+```
+
+### Step 3: Launch the conversation service
+
+Start the conversation service with the following command:
+
+```bash
+dapr run -f .
+```
+
+**Expected output**
+
+```
+== APP - conversation == Input sent: What is dapr?
+== APP - conversation == Output response: What is dapr?
+```
+
+### What happened?
+
+When you ran `dapr init` during Dapr install, the [`dapr.yaml` Multi-App Run template file]({{< ref "#dapryaml-multi-app-run-template-file" >}}) was generated in the `.dapr/components` directory. 
+
+Running `dapr run -f .` in this Quickstart started [conversation.go]({{< ref "#programcs-conversation-app" >}}).
+
+#### `dapr.yaml` Multi-App Run template file
+
+Running the [Multi-App Run template file]({{< ref multi-app-dapr-run >}}) with `dapr run -f .` starts all applications in your project. This Quickstart has only one application, so the `dapr.yaml` file contains the following: 
+
+```yml
+version: 1
+common:
+  resourcesPath: ../../components/
+apps:
+  - appDirPath: ./conversation/
+    appID: conversation
+    daprHTTPPort: 3501
+    command: ["go", "run", "."]
+```
+
+#### Echo mock LLM component
+
+In [`conversation/components`](https://github.com/dapr/quickstarts/tree/master/conversation/components) directly of the quickstart, the [`conversation.yaml` file](https://github.com/dapr/quickstarts/tree/master/conversation/components/conversation.yml) configures the echo LLM component. 
+
+```yml
+apiVersion: dapr.io/v1alpha1
+kind: Component
+metadata:
+  name: echo
+spec:
+  type: conversation.echo
+  version: v1
+```
+
+To interface with a real LLM, swap out the mock component with one of [the supported conversation components]({{< ref "supported-conversation" >}}). For example, to use an OpenAI component, see the [example in the conversation how-to guide]({{< ref "howto-conversation-layer.md#use-the-openai-component" >}})
+
+#### `conversation.go` conversation app
+
+In the application code:
+- The app sends an input "What is dapr?" to the echo mock LLM component.
+- The mock LLM echoes "What is dapr?". 
+
+```go
+package main
+
+import (
+	"context"
+	"fmt"
+	"log"
+
+	dapr "github.com/dapr/go-sdk/client"
+)
+
+func main() {
+	client, err := dapr.NewClient()
+	if err != nil {
+		panic(err)
+	}
+
+	input := dapr.ConversationInput{
+		Message: "What is dapr?",
+		// Role:     nil, // Optional
+		// ScrubPII: nil, // Optional
+	}
+
+	fmt.Println("Input sent:", input.Message)
+
+	var conversationComponent = "echo"
+
+	request := dapr.NewConversationRequest(conversationComponent, []dapr.ConversationInput{input})
+
+	resp, err := client.ConverseAlpha1(context.Background(), request)
+	if err != nil {
+		log.Fatalf("err: %v", err)
+	}
+
+	fmt.Println("Output response:", resp.Outputs[0].Result)
+}
+```
+
+{{% /codetab %}}
+
+{{< /tabs >}}
+
+## Run the app without the template
+
+{{< tabs ".NET" Go >}}
+
+ <!-- .NET -->
+{{% codetab %}}
+
+
+### Step 1: Pre-requisites
+
+For this example, you will need:
+
+- [Dapr CLI and initialized environment](https://docs.dapr.io/getting-started).
+- [.NET 8+ SDK installed](https://dotnet.microsoft.com/download).
+<!-- IGNORE_LINKS -->
+- [Docker Desktop](https://www.docker.com/products/docker-desktop)
+<!-- END_IGNORE -->
+
+### Step 2: Set up the environment
+
+Clone the [sample provided in the Quickstarts repo](https://github.com/dapr/quickstarts/tree/master/conversation).
+
+```bash
+git clone https://github.com/dapr/quickstarts.git
+```
+
+From the root of the Quickstarts directory, navigate into the conversation directory:
+
+```bash
+cd conversation/csharp/sdk/conversation
+```
+
+Install the dependencies:
+
+```bash
+dotnet build
+```
+
+### Step 3: Launch the conversation service
+
+Start the conversation service with the following command:
+
+```bash
+dapr run --app-id conversation --resources-path ../../../components/ -- dotnet run
+```
+
+**Expected output**
+
+```
+== APP - conversation == Input sent: What is dapr?
+== APP - conversation == Output response: What is dapr?
+```
+
+{{% /codetab %}}
+
+ <!-- Go -->
+{{% codetab %}}
+
+
+### Step 1: Pre-requisites
+
+For this example, you will need:
+
+- [Dapr CLI and initialized environment](https://docs.dapr.io/getting-started).
+- [Latest version of Go](https://go.dev/dl/).
+<!-- IGNORE_LINKS -->
+- [Docker Desktop](https://www.docker.com/products/docker-desktop)
+<!-- END_IGNORE -->
+
+### Step 2: Set up the environment
+
+Clone the [sample provided in the Quickstarts repo](https://github.com/dapr/quickstarts/tree/master/conversation).
+
+```bash
+git clone https://github.com/dapr/quickstarts.git
+```
+
+From the root of the Quickstarts directory, navigate into the conversation directory:
+
+```bash
+cd conversation/go/sdk/conversation
+```
+
+Install the dependencies:
+
+```bash
+go build .
+```
+
+### Step 3: Launch the conversation service
+
+Start the conversation service with the following command:
+
+```bash
+dapr run --app-id conversation --resources-path ../../../components/ -- go run .
+```
+
+**Expected output**
+
+```
+== APP - conversation == Input sent: What is dapr?
+== APP - conversation == Output response: What is dapr?
+```
+
+{{% /codetab %}}
+
+{{< /tabs >}}
+
+## Demo
+
+Watch the demo presented during [Diagrid's Dapr v1.15 celebration](https://www.diagrid.io/videos/dapr-1-15-deep-dive) to see how the conversation API works using the .NET SDK.
+
+<iframe width="560" height="315" src="https://www.youtube-nocookie.com/embed/NTnwoDhHIcQ?si=37SDcOHtEpgCIwkG&amp;start=5444" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen></iframe>
+
+## Tell us what you think!
+
+We're continuously working to improve our Quickstart examples and value your feedback. Did you find this Quickstart helpful? Do you have suggestions for improvement?
+
+Join the discussion in our [discord channel](https://discord.com/channels/778680217417809931/953427615916638238).
+
+## Next steps
+
+- HTTP samples of this quickstart:
+  - [Python](https://github.com/dapr/quickstarts/tree/master/conversation/python/http)
+  - [JavaScript](https://github.com/dapr/quickstarts/tree/master/conversation/javascript/http)
+  - [.NET](https://github.com/dapr/quickstarts/tree/master/conversation/csharp/http)
+  - [Go](https://github.com/dapr/quickstarts/tree/master/conversation/go/http)
+- Learn more about [the conversation building block]({{< ref conversation-overview.md >}})
+
+{{< button text="Explore Dapr tutorials  >>" page="getting-started/tutorials/_index.md" >}}

daprdocs/content/en/reference/components-reference/supported-conversation/deepseek.md

@@ -0,0 +1,39 @@
+---
+type: docs
+title: "DeepSeek"
+linkTitle: "DeepSeek"
+description: Detailed information on the DeepSeek conversation component
+---
+
+## Component format
+
+A Dapr `conversation.yaml` component file has the following structure:
+
+```yaml
+apiVersion: dapr.io/v1alpha1
+kind: Component
+metadata:
+  name: deepseek
+spec:
+  type: conversation.deepseek
+  metadata:
+  - name: key
+    value: mykey
+  - name: maxTokens
+    value: 2048
+```
+
+{{% alert title="Warning" color="warning" %}}
+The above example uses secrets as plain strings. It is recommended to use a secret store for the secrets, as described [here]({{< ref component-secrets.md >}}).
+{{% /alert %}}
+
+## Spec metadata fields
+
+| Field              | Required | Details | Example |
+|--------------------|:--------:|---------|---------|
+| `key`   | Y | API key for DeepSeek. | `mykey` |
+| `maxToken` | N | The max amount of tokens for each request.  | `2048` |
+
+## Related links
+
+- [Conversation API overview]({{< ref conversation-overview.md >}})

daprdocs/data/components/conversation/generic.yaml

@@ -18,3 +18,8 @@
   state: Alpha
   version: v1
   since: "1.15"
+- component: DeepSeek
+  link: deepseek
+  state: Alpha
+  version: v1
+  since: "1.15"

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