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Merge pull request #1176 from alicejgibbons/release-1.15
Re-merge 1.15 release branch into master
2 parents 43a98a1 + a70f256 commit 55d7dc2

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.github/env/global.env

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DAPR_CLI_VERSION: 1.15.0
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DAPR_RUNTIME_VERSION: 1.15.0
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DAPR_RUNTIME_VERSION: 1.15.2
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DAPR_INSTALL_URL: https://raw.githubusercontent.com/dapr/cli/v${DAPR_CLI_VERSION}/install/
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DAPR_DEFAULT_IMAGE_REGISTRY: ghcr
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conversation/csharp/http/README.md

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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.
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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.
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Visit [this](https://docs.dapr.io/developing-applications/building-blocks/conversation/conversation-overview/) link for more information about Dapr and the Conversation API.
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> **Note:** This example leverages HTTP `requests` only. If you are looking for the example using the Dapr Client SDK (recommended) [click here](../sdk/).
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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 .`.
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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/).
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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://docs.dapr.io/reference/components-reference/supported-conversation/).
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Open a new terminal window and run the multi app run template:
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conversation/csharp/sdk/README.md

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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.
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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.
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Visit [this](https://docs.dapr.io/developing-applications/building-blocks/conversation/conversation-overview/) link for more information about Dapr and the Conversation API.
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> **Note:** This example leverages the Dapr SDK. If you are looking for the example using the HTTP API [click here](../http/).
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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 .`.
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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/).
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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://docs.dapr.io/reference/components-reference/supported-conversation/).
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Open a new terminal window and run the multi app run template:
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conversation/go/http/README.md

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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.
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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.
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Visit [this](https://docs.dapr.io/developing-applications/building-blocks/conversation/conversation-overview/) link for more information about Dapr and the Conversation API.
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> **Note:** This example leverages HTTP `requests` only. If you are looking for the example using the Dapr Client SDK (recommended) [click here](../sdk/).
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This section shows how to run the application using the [multi-app run template files](https://docs.dapr.io/developing-applications/local-development/multi-app-dapr-run/multi-app-overview/) with `dapr run -f .`.
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This example uses the default LLM Component provided by Dapr which simply echoes the input provided, for testing purposes. Here are other [supported Conversation components](https://v1-15.docs.dapr.io/reference/components-reference/supported-conversation/).
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This example uses the default LLM Component provided by Dapr which simply echoes the input provided, for testing purposes. Here are other [supported Conversation components](https://docs.dapr.io/reference/components-reference/supported-conversation/).
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Open a new terminal window and run the multi app run template:
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conversation/go/sdk/README.md

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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.
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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.
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Visit [this](https://docs.dapr.io/developing-applications/building-blocks/conversation/conversation-overview/) link for more information about Dapr and the Conversation API.
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> **Note:** This example leverages the Dapr SDK. If you are looking for the example using the HTTP API [click here](../http/).
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This section shows how to run the application using the [multi-app run template files](https://docs.dapr.io/developing-applications/local-development/multi-app-dapr-run/multi-app-overview/) with `dapr run -f .`.
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This example uses the default LLM Component provided by Dapr which simply echoes the input provided, for testing purposes. Here are other [supported Conversation components](https://v1-15.docs.dapr.io/reference/components-reference/supported-conversation/).
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This example uses the default LLM Component provided by Dapr which simply echoes the input provided, for testing purposes. Here are other [supported Conversation components](https://docs.dapr.io/reference/components-reference/supported-conversation/).
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Open a new terminal window and run the multi app run template:
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conversation/javascript/http/README.md

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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.
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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.
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Visit [this](https://docs.dapr.io/developing-applications/building-blocks/conversation/conversation-overview/) link for more information about Dapr and the Conversation API.
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> **Note:** This example leverages HTTP `requests` only.
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This section shows how to run the application using the [multi-app run template files](https://docs.dapr.io/developing-applications/local-development/multi-app-dapr-run/multi-app-overview/) with `dapr run -f .`.
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This example uses the default LLM Component provided by Dapr which simply echoes the input provided, for testing purposes. Here are other [supported Conversation components](https://v1-15.docs.dapr.io/reference/components-reference/supported-conversation/).
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This example uses the default LLM Component provided by Dapr which simply echoes the input provided, for testing purposes. Here are other [supported Conversation components](https://docs.dapr.io/reference/components-reference/supported-conversation/).
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1. Install dependencies:
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conversation/python/http/README.md

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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.
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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.
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Visit [this](https://docs.dapr.io/developing-applications/building-blocks/conversation/conversation-overview/) link for more information about Dapr and the Conversation API.
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> **Note:** This example leverages HTTP `requests` only.
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This section shows how to run the application using the [multi-app run template files](https://docs.dapr.io/developing-applications/local-development/multi-app-dapr-run/multi-app-overview/) with `dapr run -f .`.
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This example uses the default LLM Component provided by Dapr which simply echoes the input provided, for testing purposes. Here are other [supported Conversation components](https://v1-15.docs.dapr.io/reference/components-reference/supported-conversation/).
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This example uses the default LLM Component provided by Dapr which simply echoes the input provided, for testing purposes. Here are other [supported Conversation components](https://docs.dapr.io/reference/components-reference/supported-conversation/).
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1. Install dependencies:
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conversation/python/sdk/README.md

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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.
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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.
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Visit [this](https://docs.dapr.io/developing-applications/building-blocks/conversation/conversation-overview/) link for more information about Dapr and the Conversation API.
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This quickstart includes one app:
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This section shows how to run the application using the [multi-app run template files](https://docs.dapr.io/developing-applications/local-development/multi-app-dapr-run/multi-app-overview/) with `dapr run -f .`.
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This example uses the default LLM Component provided by Dapr which simply echoes the input provided, for testing purposes. Here are other [supported Conversation components](https://v1-15.docs.dapr.io/reference/components-reference/supported-conversation/).
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This example uses the default LLM Component provided by Dapr which simply echoes the input provided, for testing purposes. Here are other [supported Conversation components](https://docs.dapr.io/reference/components-reference/supported-conversation/).
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1. Install dependencies:
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jobs/csharp/http/README.md

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expected_stderr_lines:
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output_match_mode: substring
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match_order: none
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background: false
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background: true
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sleep: 60
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timeout_seconds: 120
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-->
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<!-- END_STEP -->
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3. Stop and clean up application processes.
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<!-- STEP
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name: Stop multi-app run
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-->
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```bash
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dapr stop -f .
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```
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<!-- END_STEP -->
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## Run apps individually
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### Schedule Jobs

jobs/csharp/http/job-scheduler/Program.cs

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var daprHost = Environment.GetEnvironmentVariable("DAPR_HOST") ?? "http://localhost";
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var jobServiceDaprHttpPort = "6280";
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var httpClient = new HttpClient();
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await Task.Delay(5000); // Wait for job-service to start
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async Task GetJobDetails(string jobName)
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{
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var reqURL = $"{daprHost}:{jobServiceDaprHttpPort}/v1.0-alpha1/jobs/{jobName}";
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var response = await httpClient.GetAsync(reqURL);
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if (!response.IsSuccessStatusCode)

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