Csharp conversation API quickstarts

conversation/csharp/http/README.md

@@ -0,0 +1,85 @@
+# Dapr Conversation API (C# HTTP)
+
+In this quickstart, you'll send an input to a mock Large Language Model (LLM) using Dapr's Conversation API. This API is responsible for providing one consistent API entry point to talk to underlying LLM providers.
+
+Visit [this](https://v1-15.docs.dapr.io/developing-applications/building-blocks/conversation/conversation-overview/) link for more information about Dapr and the Conversation API.
+
+> **Note:** This example leverages HTTP `requests` only.  If you are looking for the example using the Dapr Client SDK (recommended) [click here](../sdk/).
+
+This quickstart includes one app:
+
+- Conversation, responsible for sending an input to the underlying LLM and retrieving an output.
+
+## Run the app with the template file
+
+This section shows how to run the application using the [multi-app run template file](https://docs.dapr.io/developing-applications/local-development/multi-app-dapr-run/multi-app-overview/) and Dapr CLI with `dapr run -f .`.  
+
+This example uses the default LLM Component provided by Dapr which simply echoes the input provided, for testing purposes. Integrate with popular LLM models by using one of the other [supported conversation components](https://v1-15.docs.dapr.io/reference/components-reference/supported-conversation/).
+
+Open a new terminal window and run the multi app run template:
+
+<!-- STEP
+name: Run multi app run template
+expected_stdout_lines:
+  - '== APP - conversation == Input sent: What is dapr?'
+  - '== APP - conversation == Output response: What is dapr?'
+expected_stderr_lines:
+output_match_mode: substring
+match_order: none
+background: true
+sleep: 15
+timeout_seconds: 15
+-->
+
+```bash
+dapr run -f .
+```
+
+The terminal console output should look similar to this, where:
+
+- The app sends an input `What is dapr?` to the `echo` Component mock LLM.
+- The mock LLM echoes `What is dapr?`.
+
+```text
+== APP - conversation == Input sent: What is dapr?
+== APP - conversation == Output response: What is dapr?
+```
+
+<!-- END_STEP -->
+
+2. Stop and clean up application processes.
+
+<!-- STEP
+name: Stop multi-app run
+-->
+
+```bash
+dapr stop -f .
+```
+
+<!-- END_STEP -->
+
+## Run the app individually
+
+1. Open a terminal and run the `conversation` app. Build the dependencies if you haven't already.
+
+```bash
+cd ./conversation
+dotnet build
+```
+
+2. Run the Dapr process alongside the application.
+
+```bash
+dapr run --app-id conversation --resources-path ../../../components/ -- dotnet run
+```
+
+The terminal console output should look similar to this, where:
+
+- The app sends an input `What is dapr?` to the `echo` Component mock LLM.
+- The mock LLM echoes `What is dapr?`.
+
+```text
+== APP - conversation == Input sent: What is dapr?
+== APP - conversation == Output response: What is dapr?
+```

conversation/csharp/http/conversation/Program.cs

@@ -0,0 +1,67 @@
+/*
+Copyright 2024 The Dapr Authors
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+	http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+*/
+
+using System.Net.Http;
+using System.Text.Json;
+using System.Text;
+
+class Program
+{
+  private const string ConversationComponentName = "echo";
+
+  static async Task Main(string[] args)
+  {
+    var daprHost = Environment.GetEnvironmentVariable("DAPR_HOST") ?? "http://localhost";
+    var daprHttpPort = Environment.GetEnvironmentVariable("DAPR_HTTP_PORT") ?? "3500";
+
+    var client = new HttpClient
+    {
+      Timeout = TimeSpan.FromSeconds(15)
+    };
+
+    var inputBody = new
+    {
+      name = "echo",
+      inputs = new[] { new { message = "What is dapr?" } },
+      parameters = new { },
+      metadata = new { }
+    };
+
+    var daprUrl = $"{daprHost}:{daprHttpPort}/v1.0-alpha1/conversation/{ConversationComponentName}/converse";
+
+    try
+    {
+      var content = new StringContent(JsonSerializer.Serialize(inputBody), Encoding.UTF8, "application/json");
+
+      // Send a request to the echo mock LLM component
+      var response = await client.PostAsync(daprUrl, content);
+      response.EnsureSuccessStatusCode();
+
+      Console.WriteLine("Input sent: " + inputBody.inputs[0].message);
+
+      var responseBody = await response.Content.ReadAsStringAsync();
+
+      // Parse the response
+      var data = JsonSerializer.Deserialize<Dictionary<string, List<Dictionary<string, string>>>>(responseBody);
+      var result = data?["outputs"]?[0]?["result"];
+
+      Console.WriteLine("Output response: " + result);
+    }
+    catch (Exception ex)
+    {
+      Console.WriteLine("Error: " + ex.Message);
+    }
+  }
+}

conversation/csharp/http/conversation/Program.csproj

@@ -0,0 +1,14 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFramework>net8.0</TargetFramework>
+    <ImplicitUsings>enable</ImplicitUsings>
+    <Nullable>enable</Nullable>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="System.Text.Json" Version="9.0.1" />
+  </ItemGroup>
+
+</Project>

conversation/csharp/http/dapr.yaml

@@ -0,0 +1,8 @@
+version: 1
+common:
+  resourcesPath: ../../components/
+apps:
+  - appDirPath: ./conversation/
+    appID: conversation
+    daprHTTPPort: 3500
+    command: ["dotnet", "run"]

conversation/csharp/http/makefile

@@ -0,0 +1,2 @@
+include ../../../docker.mk
+include ../../../validate.mk

conversation/csharp/sdk/README.md

@@ -0,0 +1,85 @@
+# Dapr Conversation API (C# SDK)
+
+In this quickstart, you'll send an input to a mock Large Language Model (LLM) using Dapr's Conversation API. This API is responsible for providing one consistent API entry point to talk to underlying LLM providers.
+
+Visit [this](https://v1-15.docs.dapr.io/developing-applications/building-blocks/conversation/conversation-overview/) link for more information about Dapr and the Conversation API.
+
+> **Note:** This example leverages the Dapr SDK. If you are looking for the example using the HTTP API [click here](../http/).
+
+This quickstart includes one app:
+
+- Conversation, responsible for sending an input to the underlying LLM and retrieving an output.
+
+## Run the app with the template file
+
+This section shows how to run the application using the [multi-app run template file](https://docs.dapr.io/developing-applications/local-development/multi-app-dapr-run/multi-app-overview/) and Dapr CLI with `dapr run -f .`.  
+
+This example uses the default LLM Component provided by Dapr which simply echoes the input provided, for testing purposes. Integrate with popular LLM models by using one of the other [supported conversation components](https://v1-15.docs.dapr.io/reference/components-reference/supported-conversation/).
+
+Open a new terminal window and run the multi app run template:
+
+<!-- STEP
+name: Run multi app run template
+expected_stdout_lines:
+  - '== APP - conversation == Input sent: What is dapr?'
+  - '== APP - conversation == Output response: What is dapr?'
+expected_stderr_lines:
+output_match_mode: substring
+match_order: none
+background: true
+sleep: 15
+timeout_seconds: 15
+-->
+
+```bash
+dapr run -f .
+```
+
+The terminal console output should look similar to this, where:
+
+- The app sends an input `What is dapr?` to the `echo` Component mock LLM.
+- The mock LLM echoes `What is dapr?`.
+
+```text
+== APP - conversation == Input sent: What is dapr?
+== APP - conversation == Output response: What is dapr?
+```
+
+<!-- END_STEP -->
+
+2. Stop and clean up application processes.
+
+<!-- STEP
+name: Stop multi-app run
+-->
+
+```bash
+dapr stop -f .
+```
+
+<!-- END_STEP -->
+
+## Run the app individually
+
+1. Open a terminal and run the `conversation` app. Build the dependencies if you haven't already.
+
+```bash
+cd ./conversation
+dotnet build
+```
+
+2. Run the Dapr process alongside the application.
+
+```bash
+dapr run --app-id conversation --resources-path ../../../components/ -- dotnet run
+```
+
+The terminal console output should look similar to this, where:
+
+- The app sends an input `What is dapr?` to the `echo` Component mock LLM.
+- The mock LLM echoes `What is dapr?`.
+
+```text
+== APP - conversation == Input sent: What is dapr?
+== APP - conversation == Output response: What is dapr?
+```

conversation/csharp/sdk/conversation/Program.cs

@@ -0,0 +1,54 @@
+/*
+Copyright 2024 The Dapr Authors
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+	http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+*/
+
+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);
+    }
+  }
+}

conversation/csharp/sdk/conversation/Program.csproj

@@ -0,0 +1,14 @@
+<Project Sdk="Microsoft.NET.Sdk.Web">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFramework>net8.0</TargetFramework>
+    <ImplicitUsings>enable</ImplicitUsings>
+    <Nullable>enable</Nullable>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Dapr.AI" Version="1.15.0-rc02" />
+  </ItemGroup>
+
+</Project>

conversation/csharp/sdk/dapr.yaml

@@ -0,0 +1,8 @@
+version: 1
+common:
+  resourcesPath: ../../components/
+apps:
+  - appDirPath: ./conversation/
+    appID: conversation
+    daprHTTPPort: 3500
+    command: ["dotnet", "run"]

conversation/csharp/sdk/makefile

@@ -0,0 +1,2 @@
+include ../../../docker.mk
+include ../../../validate.mk

conversation/go/http/README.md

@@ -4,11 +4,11 @@ In this quickstart, you'll send an input to a mock Large Language Model (LLM) us
 
 Visit [this](https://v1-15.docs.dapr.io/developing-applications/building-blocks/conversation/conversation-overview/) link for more information about Dapr and the Conversation API.
 
-> **Note:** This example leverages HTTP `requests` only.  If you are looking for the example using the Dapr Client SDK (recommended) [click here](../sdk/).
+> **Note:** This example leverages HTTP `requests` only. If you are looking for the example using the Dapr Client SDK (recommended) [click here](../sdk/).
 
 This quickstart includes one app:
 
-- `conversation.go`, responsible for sending and input to the underlying LLM and retrieving an output.
+- `conversation.go`, responsible for sending an input to the underlying LLM and retrieving an output.
 
 ## Run the app with the template file
 
@@ -47,7 +47,7 @@ The terminal console output should look similar to this, where:
 
 <!-- END_STEP -->
 
-2. Stop and clean up application processes
+2. Stop and clean up application processes.
 
 <!-- STEP
 name: Stop multi-app run 

conversation/go/sdk/README.md

@@ -4,11 +4,11 @@ In this quickstart, you'll send an input to a mock Large Language Model (LLM) us
 
 Visit [this](https://v1-15.docs.dapr.io/developing-applications/building-blocks/conversation/conversation-overview/) link for more information about Dapr and the Conversation API.
 
-> **Note:** This example leverages the Dapr SDK.  If you are looking for the example using the HTTP API [click here](../http/).
+> **Note:** This example leverages the Dapr SDK. If you are looking for the example using the HTTP API [click here](../http/).
 
 This quickstart includes one app:
 
-- `conversation.go`, responsible for sending and input to the underlying LLM and retrieving an output.
+- `conversation.go`, responsible for sending an input to the underlying LLM and retrieving an output.
 
 ## Run the app with the template file
 
@@ -47,7 +47,7 @@ The terminal console output should look similar to this, where:
 
 <!-- END_STEP -->
 
-2. Stop and clean up application processes
+2. Stop and clean up application processes.
 
 <!-- STEP
 name: Stop multi-app run