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Merge branch 'v1.16' into remove-python-submodule
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‎.gitmodules‎

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[submodule "sdkdocs/go"]
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path = sdkdocs/go
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url = https://github.com/dapr/go-sdk.git
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[submodule "sdkdocs/java"]
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path = sdkdocs/java
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url = https://github.com/dapr/java-sdk.git
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[submodule "sdkdocs/js"]
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path = sdkdocs/js
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url = https://github.com/dapr/js-sdk.git

‎hugo.yaml‎

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- source: sdkdocs/go/daprdocs/content/en/go-sdk-contributing
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target: content/contributing/sdk-contrib/
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lang: en
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- source: sdkdocs/java/daprdocs/content/en/java-sdk-docs
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- source: sdkdocs/java/content/en/java-sdk-docs
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target: content/developing-applications/sdks/java
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lang: en
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- source: sdkdocs/java/daprdocs/content/en/java-sdk-contributing
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- source: sdkdocs/java/content/en/java-sdk-contributing
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target: content/contributing/sdk-contrib/
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lang: en
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- source: sdkdocs/js/daprdocs/content/en/js-sdk-docs

‎sdkdocs/java‎

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‎sdkdocs/java/content/en/java-sdk-contributing/java-contributing.md‎

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---
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type: docs
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title: "Contributing to the Java SDK"
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linkTitle: "Java SDK"
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weight: 3000
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description: Guidelines for contributing to the Dapr Java SDK
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---
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When contributing to the [Java SDK](https://github.com/dapr/java-sdk) the following rules and best-practices should be followed.
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## Examples
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The `examples` directory contains code samples for users to run to try out specific functionality of the various Java SDK packages and extensions. When writing new and updated samples keep in mind:
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- All examples should be runnable on Windows, Linux, and MacOS. While Java code is consistent among operating systems, any pre/post example commands should provide options through [tabpane]({{% ref "contributing-docs.md#tabbed-content" %}})
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- Contain steps to download/install any required pre-requisites. Someone coming in with a fresh OS install should be able to start on the example and complete it without an error. Links to external download pages are fine.
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## Docs
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The `daprdocs` directory contains the markdown files that are rendered into the [Dapr Docs](https://docs.dapr.io) website. When the documentation website is built, this repo is cloned and configured so that its contents are rendered with the docs content. When writing docs, keep in mind:
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- All rules in the [docs guide]({{% ref contributing-docs.md %}}) should be followed in addition to these.
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- All files and directories should be prefixed with `java-` to ensure all file/directory names are globally unique across all Dapr documentation.
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## Github Dapr Bot Commands
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Checkout the [daprbot documentation](https://docs.dapr.io/contributing/daprbot/) for Github commands you can run in this repo for common tasks. For example, you can run the `/assign` (as a comment on an issue) to assign the issue to yourself.

‎sdkdocs/java/content/en/java-sdk-docs/_index.md‎

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---
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type: docs
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title: "Dapr Java SDK"
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linkTitle: "Java"
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weight: 1000
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description: Java SDK packages for developing Dapr applications
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cascade:
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github_repo: https://github.com/dapr/java-sdk
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github_subdir: daprdocs/content/en/java-sdk-docs
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path_base_for_github_subdir: content/en/developing-applications/sdks/java/
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github_branch: master
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---
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Dapr offers a variety of packages to help with the development of Java applications. Using them you can create Java clients, servers, and virtual actors with Dapr.
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## Prerequisites
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- [Dapr CLI]({{% ref install-dapr-cli.md %}}) installed
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- Initialized [Dapr environment]({{% ref install-dapr-selfhost.md %}})
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- JDK 11 or above - the published jars are compatible with Java 8:
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- [AdoptOpenJDK 11 - LTS](https://adoptopenjdk.net/)
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- [Oracle's JDK 15](https://www.oracle.com/java/technologies/javase-downloads.html)
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- [Oracle's JDK 11 - LTS](https://www.oracle.com/java/technologies/javase-jdk11-downloads.html)
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- [OpenJDK](https://openjdk.java.net/)
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- Install one of the following build tools for Java:
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- [Maven 3.x](https://maven.apache.org/install.html)
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- [Gradle 6.x](https://gradle.org/install/)
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## Import Dapr's Java SDK
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Next, import the Java SDK packages to get started. Select your preferred build tool to learn how to import.
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{{< tabpane text=true >}}
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{{% tab header="Maven" %}}
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<!--Maven-->
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For a Maven project, add the following to your `pom.xml` file:
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```xml
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<project>
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...
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<dependencies>
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...
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<!-- Dapr's core SDK with all features, except Actors. -->
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<dependency>
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<groupId>io.dapr</groupId>
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<artifactId>dapr-sdk</artifactId>
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<version>1.16.0</version>
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</dependency>
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<!-- Dapr's SDK for Actors (optional). -->
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<dependency>
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<groupId>io.dapr</groupId>
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<artifactId>dapr-sdk-actors</artifactId>
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<version>1.16.0</version>
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</dependency>
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<!-- Dapr's SDK integration with SpringBoot (optional). -->
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<dependency>
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<groupId>io.dapr</groupId>
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<artifactId>dapr-sdk-springboot</artifactId>
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<version>1.16.0</version>
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</dependency>
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...
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</dependencies>
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...
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</project>
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```
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{{% /tab %}}
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{{% tab header="Gradle" %}}
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<!--Gradle-->
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For a Gradle project, add the following to your `build.gradle` file:
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```java
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dependencies {
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...
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// Dapr's core SDK with all features, except Actors.
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compile('io.dapr:dapr-sdk:1.16.0')
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// Dapr's SDK for Actors (optional).
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compile('io.dapr:dapr-sdk-actors:1.16.0')
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// Dapr's SDK integration with SpringBoot (optional).
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compile('io.dapr:dapr-sdk-springboot:1.16.0')
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}
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```
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{{% /tab %}}
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{{< /tabpane >}}
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If you are also using Spring Boot, you may run into a common issue where the `OkHttp` version that the Dapr SDK uses conflicts with the one specified in the Spring Boot _Bill of Materials_.
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You can fix this by specifying a compatible `OkHttp` version in your project to match the version that the Dapr SDK uses:
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```xml
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<dependency>
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<groupId>com.squareup.okhttp3</groupId>
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<artifactId>okhttp</artifactId>
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<version>1.16.0</version>
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</dependency>
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```
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## Try it out
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Put the Dapr Java SDK to the test. Walk through the Java quickstarts and tutorials to see Dapr in action:
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| SDK samples | Description |
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| ----------- | ----------- |
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| [Quickstarts]({{% ref quickstarts %}}) | Experience Dapr's API building blocks in just a few minutes using the Java SDK. |
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| [SDK samples](https://github.com/dapr/java-sdk/tree/master/examples) | Clone the SDK repo to try out some examples and get started. |
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```java
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import io.dapr.client.DaprClient;
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import io.dapr.client.DaprClientBuilder;
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try (DaprClient client = (new DaprClientBuilder()).build()) {
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// sending a class with message; BINDING_OPERATION="create"
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client.invokeBinding(BINDING_NAME, BINDING_OPERATION, myClass).block();
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// sending a plain string
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client.invokeBinding(BINDING_NAME, BINDING_OPERATION, message).block();
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}
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```
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- For a full guide on output bindings visit [How-To: Output bindings]({{% ref howto-bindings.md %}}).
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- Visit [Java SDK examples](https://github.com/dapr/java-sdk/tree/master/examples/src/main/java/io/dapr/examples/bindings/http) for code samples and instructions to try out output bindings.
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## Available packages
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<div class="card-deck">
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<div class="card">
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<div class="card-body">
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<h5 class="card-title"><b>Client</b></h5>
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<p class="card-text">Create Java clients that interact with a Dapr sidecar and other Dapr applications.</p>
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<a href="{{% ref java-client %}}" class="stretched-link"></a>
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</div>
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</div>
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<div class="card">
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<div class="card-body">
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<h5 class="card-title"><b>Workflow</b></h5>
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<p class="card-text">Create and manage workflows that work with other Dapr APIs in Java.</p>
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<a href="{{% ref workflow %}}" class="stretched-link"></a>
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</div>
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</div>
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</div>

‎sdkdocs/java/content/en/java-sdk-docs/java-ai/_index.md‎

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---
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type: docs
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title: "AI"
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linkTitle: "AI"
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weight: 3000
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description: With the Dapr Conversation AI package, you can interact with the Dapr AI workloads from a Java application. To get started, walk through the [Dapr AI]({{% ref java-ai-howto.md %}}) how-to guide.
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---

‎sdkdocs/java/content/en/java-sdk-docs/java-ai/java-ai-howto.md‎

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---
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type: docs
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title: "How to: Author and manage Dapr Conversation AI in the Java SDK"
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linkTitle: "How to: Author and manage Conversation AI"
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weight: 20000
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description: How to get up and running with Conversation AI using the Dapr Java SDK
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---
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As part of this demonstration, we will look at how to use the Conversation API to converse with a Large Language Model (LLM). The API
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will return the response from the LLM for the given prompt. With the [provided conversation ai example](https://github.com/dapr/java-sdk/tree/master/examples/src/main/java/io/dapr/examples/conversation), you will:
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- You will provide a prompt using the [Conversation AI example](https://github.com/dapr/java-sdk/blob/master/examples/src/main/java/io/dapr/examples/conversation/DemoConversationAI.java)
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- Filter out Personally identifiable information (PII).
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This example uses the default configuration from `dapr init` in [self-hosted mode](https://github.com/dapr/cli#install-dapr-on-your-local-machine-self-hosted).
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## Prerequisites
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- [Dapr CLI and initialized environment](https://docs.dapr.io/getting-started).
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- Java JDK 11 (or greater):
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- [Oracle JDK](https://www.oracle.com/java/technologies/downloads), or
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- OpenJDK
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- [Apache Maven](https://maven.apache.org/install.html), version 3.x.
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- [Docker Desktop](https://www.docker.com/products/docker-desktop)
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## Set up the environment
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Clone the [Java SDK repo](https://github.com/dapr/java-sdk) and navigate into it.
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```bash
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git clone https://github.com/dapr/java-sdk.git
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cd java-sdk
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```
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Run the following command to install the requirements for running the Conversation AI example with the Dapr Java SDK.
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```bash
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mvn clean install -DskipTests
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```
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From the Java SDK root directory, navigate to the examples' directory.
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```bash
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cd examples
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```
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Run the Dapr sidecar.
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```sh
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dapr run --app-id conversationapp --dapr-grpc-port 51439 --dapr-http-port 3500 --app-port 8080
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```
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> Now, Dapr is listening for HTTP requests at `http://localhost:3500` and gRPC requests at `http://localhost:51439`.
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## Send a prompt with Personally identifiable information (PII) to the Conversation AI API
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In the `DemoConversationAI` there are steps to send a prompt using the `converse` method under the `DaprPreviewClient`.
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```java
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public class DemoConversationAI {
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/**
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* The main method to start the client.
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*
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* @param args Input arguments (unused).
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*/
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public static void main(String[] args) {
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try (DaprPreviewClient client = new DaprClientBuilder().buildPreviewClient()) {
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System.out.println("Sending the following input to LLM: Hello How are you? This is the my number 672-123-4567");
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ConversationInput daprConversationInput = new ConversationInput("Hello How are you? "
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+ "This is the my number 672-123-4567");
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// Component name is the name provided in the metadata block of the conversation.yaml file.
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Mono<ConversationResponse> responseMono = client.converse(new ConversationRequest("echo",
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List.of(daprConversationInput))
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.setContextId("contextId")
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.setScrubPii(true).setTemperature(1.1d));
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ConversationResponse response = responseMono.block();
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System.out.printf("Conversation output: %s", response.getConversationOutputs().get(0).getResult());
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} catch (Exception e) {
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throw new RuntimeException(e);
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}
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}
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}
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```
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Run the `DemoConversationAI` with the following command.
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```sh
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java -jar target/dapr-java-sdk-examples-exec.jar io.dapr.examples.conversation.DemoConversationAI
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```
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### Sample output
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```
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== APP == Conversation output: Hello How are you? This is the my number <ISBN>
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```
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As shown in the output, the number sent to the API is obfuscated and returned in the form of <ISBN>.
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The example above uses an ["echo"](https://docs.dapr.io/developing-applications/building-blocks/conversation/howto-conversation-layer/#set-up-the-conversation-component)
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component for testing, which simply returns the input message.
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When integrated with LLMs like OpenAI or Claude, you’ll receive meaningful responses instead of echoed input.
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## Next steps
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- [Learn more about Conversation AI]({{% ref conversation-overview.md %}})
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- [Conversation AI API reference]({{% ref conversation_api.md %}})

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