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tweak some things 

Signed-off-by: Hannah Hunter <hannahhunter@microsoft.com>
This commit is contained in:
Hannah Hunter 2025-01-17 15:28:29 -05:00
parent 6c41e3f444
commit 99a449f6f5
1 changed files with 2 additions and 9 deletions
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11
daprdocs/content/en/getting-started/quickstarts/conversation-quickstart.md
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@ -10,12 +10,7 @@ description: Get started with the Dapr conversation building block
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 >}})
You can try out this conversation quickstart by either:
- [Running all applications in this sample simultaneously with the Multi-App Run template file]({{< ref "#run-using-multi-app-run" >}}), or
- [Running one application at a time]({{< ref "#run-one-job-application-at-a-time" >}})
Let's take a look at how the [Dapr conversation building block]({{< ref conversation-overview.md >}}) makes interacting with the Anthropic LLM easier. In this quickstart, you use the Anthropic component to communicate with the LLM and ask it for a poem about Dapr.
{{< tabs ".NET" >}}
@ -101,7 +96,6 @@ Exited App successfully
### What happened?
#### `conversation.yaml` 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 Anthropic LLM component.
@ -139,13 +133,12 @@ var app = builder.Build();
var conversationClient = app.Services.GetRequiredService<DaprConversationClient>();
var logger = app.Services.GetRequiredService<ILogger<Program>>();
// Set prompt to send to the Anthropic LLM
// Send prompt to send to the Anthropic LLM
const string prompt = "Please write a witty sonnet about the Dapr distributed programming framework at dapr.io";
var response = await conversationClient.ConverseAsync("conversation",
[new(prompt, DaprConversationRole.Generic)]);
Log.LogRequest(logger, prompt);
// Send prompt to LLM
var stringBuilder = new StringBuilder();
foreach (var resp in response.Outputs)
{