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Csharp conversation API quickstarts
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85 changes: 85 additions & 0 deletions conversation/csharp/http/README.md
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# 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?
```
67 changes: 67 additions & 0 deletions conversation/csharp/http/conversation/Program.cs
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/*
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);
}
}
}
14 changes: 14 additions & 0 deletions conversation/csharp/http/conversation/Program.csproj
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<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>
8 changes: 8 additions & 0 deletions conversation/csharp/http/dapr.yaml
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version: 1
common:
resourcesPath: ../../components/
apps:
- appDirPath: ./conversation/
appID: conversation
daprHTTPPort: 3500
command: ["dotnet", "run"]
2 changes: 2 additions & 0 deletions conversation/csharp/http/makefile
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include ../../../docker.mk
include ../../../validate.mk
85 changes: 85 additions & 0 deletions conversation/csharp/sdk/README.md
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# 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?
```
54 changes: 54 additions & 0 deletions conversation/csharp/sdk/conversation/Program.cs
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/*
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);
}
}
}
14 changes: 14 additions & 0 deletions conversation/csharp/sdk/conversation/Program.csproj
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<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>
8 changes: 8 additions & 0 deletions conversation/csharp/sdk/dapr.yaml
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version: 1
common:
resourcesPath: ../../components/
apps:
- appDirPath: ./conversation/
appID: conversation
daprHTTPPort: 3500
command: ["dotnet", "run"]
2 changes: 2 additions & 0 deletions conversation/csharp/sdk/makefile
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include ../../../docker.mk
include ../../../validate.mk
6 changes: 3 additions & 3 deletions conversation/go/http/README.md
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Expand Up @@ -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

Expand Down Expand Up @@ -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
Expand Down
6 changes: 3 additions & 3 deletions conversation/go/sdk/README.md
Original file line number Diff line number Diff line change
Expand Up @@ -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

Expand Down Expand Up @@ -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
Expand Down

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