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‎examples/src/main/java/io/dapr/examples/conversation/AssistantMessageDemo.java

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/*
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* Copyright 2021 The Dapr Authors
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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* http://www.apache.org/licenses/LICENSE-2.0
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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limitations under the License.
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*/
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package io.dapr.examples.conversation;
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import io.dapr.client.DaprClientBuilder;
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import io.dapr.client.DaprPreviewClient;
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import io.dapr.client.domain.AssistantMessage;
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import io.dapr.client.domain.ConversationInputAlpha2;
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import io.dapr.client.domain.ConversationMessage;
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import io.dapr.client.domain.ConversationMessageContent;
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import io.dapr.client.domain.ConversationRequestAlpha2;
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import io.dapr.client.domain.ConversationResponseAlpha2;
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import io.dapr.client.domain.ConversationResultAlpha2;
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import io.dapr.client.domain.ConversationResultChoices;
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import io.dapr.client.domain.ConversationToolCalls;
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import io.dapr.client.domain.ConversationToolCallsOfFunction;
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import io.dapr.client.domain.SystemMessage;
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import io.dapr.client.domain.ToolMessage;
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import io.dapr.client.domain.UserMessage;
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import reactor.core.publisher.Mono;
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import java.util.ArrayList;
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import java.util.List;
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public class AssistantMessageDemo {
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/**
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* The main method to demonstrate conversation AI with assistant messages and conversation history.
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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("Demonstrating Conversation AI with Assistant Messages and Conversation History");
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// Create a conversation history with multiple message types
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List<ConversationMessage> conversationHistory = new ArrayList<>();
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// 1. System message to set context
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SystemMessage systemMessage = new SystemMessage(List.of(
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new ConversationMessageContent("You are a helpful assistant that can help with weather queries.")
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));
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systemMessage.setName("WeatherBot");
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conversationHistory.add(systemMessage);
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// 2. Initial user greeting
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UserMessage greeting = new UserMessage(List.of(
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new ConversationMessageContent("Hello! I need help with weather information.")
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));
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greeting.setName("User123");
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conversationHistory.add(greeting);
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// 3. Assistant response with tool call
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AssistantMessage assistantResponse = new AssistantMessage(
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List.of(new ConversationMessageContent("I'll help you with weather information. Let me check the weather for you.")),
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List.of(new ConversationToolCalls(
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new ConversationToolCallsOfFunction("get_weather", "{\"location\": \"San Francisco\", \"unit\": \"fahrenheit\"}")
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))
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);
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assistantResponse.setName("WeatherBot");
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conversationHistory.add(assistantResponse);
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// 4. Tool response (simulating weather API response)
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ToolMessage toolResponse = new ToolMessage(List.of(
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new ConversationMessageContent("{\"temperature\": \"72F\", \"condition\": \"sunny\", \"humidity\": \"65%\"}")
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));
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toolResponse.setName("weather_api");
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conversationHistory.add(toolResponse);
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// 5. Current user question
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UserMessage currentQuestion = new UserMessage(List.of(
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new ConversationMessageContent("Based on that weather data, should I wear a jacket today?")
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));
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currentQuestion.setName("User123");
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conversationHistory.add(currentQuestion);
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// Create conversation input with the full history
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ConversationInputAlpha2 conversationInput = new ConversationInputAlpha2(conversationHistory);
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conversationInput.setScrubPii(false);
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// Create the conversation request
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ConversationRequestAlpha2 request = new ConversationRequestAlpha2("echo", List.of(conversationInput))
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.setContextId("assistant-demo-context")
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.setTemperature(0.8d);
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// Send the request
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System.out.println("Sending conversation with assistant messages and history...");
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System.out.println("Conversation includes:");
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System.out.println("- System message (context setting)");
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System.out.println("- User greeting");
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System.out.println("- Assistant response with tool call");
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System.out.println("- Tool response with weather data");
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System.out.println("- User follow-up question");
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Mono<ConversationResponseAlpha2> responseMono = client.converseAlpha2(request);
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ConversationResponseAlpha2 response = responseMono.block();
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// Process and display the response
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if (response != null && response.getOutputs() != null && !response.getOutputs().isEmpty()) {
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ConversationResultAlpha2 result = response.getOutputs().get(0);
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if (result.getChoices() != null && !result.getChoices().isEmpty()) {
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ConversationResultChoices choice = result.getChoices().get(0);
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if (choice.getMessage() != null && choice.getMessage().getContent() != null) {
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System.out.printf("Assistant Response: %s%n", choice.getMessage().getContent());
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}
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// Check for additional tool calls in the response
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if (choice.getMessage() != null && choice.getMessage().getToolCalls() != null) {
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System.out.println("Assistant requested additional tool calls:");
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choice.getMessage().getToolCalls().forEach(toolCall -> {
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System.out.printf("Tool: %s, Arguments: %s%n",
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toolCall.getFunction().getName(),
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toolCall.getFunction().getArguments());
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});
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}
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}
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}
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System.out.println("Assistant message demonstration completed.");
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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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}

‎examples/src/main/java/io/dapr/examples/conversation/DemoConversationAI.java

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This file was deleted.

‎examples/src/main/java/io/dapr/examples/conversation/README.md

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@@ -45,30 +45,51 @@ Run `dapr init` to initialize Dapr in Self-Hosted Mode if it's not already initi
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### Running the example
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This example uses the Java SDK Dapr client in order to **Converse** with an LLM.
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`DemoConversationAI.java` is the example class demonstrating these features.
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`UserMessageDemo.java` is the example class demonstrating these features.
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Kindly check [DaprPreviewClient.java](https://github.com/dapr/java-sdk/blob/master/sdk/src/main/java/io/dapr/client/DaprPreviewClient.java) for a detailed description of the supported APIs.
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```java
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public class DemoConversationAI {
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public class UserMessageDemo {
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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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Map<Property<?>, String> overrides = Map.of(
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Properties.HTTP_PORT, "3500",
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Properties.GRPC_PORT, "50001"
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);
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try (DaprPreviewClient client = new DaprClientBuilder().withPropertyOverrides(overrides).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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// Create user message with content
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UserMessage userMessage = new UserMessage(List.of(new ConversationMessageContent("Hello How are you? "
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+ "This is the my number 672-123-4567")));
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// Create conversation input with the user message
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ConversationInputAlpha2 daprConversationInput = new ConversationInputAlpha2(List.of(userMessage));
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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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Mono<ConversationResponseAlpha2> responseMono = client.converseAlpha2(new ConversationRequestAlpha2("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.getConversationOutpus().get(0).getResult());
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.setScrubPii(true)
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.setTemperature(1.1d));
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ConversationResponseAlpha2 response = responseMono.block();
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// Extract and print the conversation result
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if (response != null && response.getOutputs() != null && !response.getOutputs().isEmpty()) {
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ConversationResultAlpha2 result = response.getOutputs().get(0);
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if (result.getChoices() != null && !result.getChoices().isEmpty()) {
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ConversationResultChoices choice = result.getChoices().get(0);
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if (choice.getMessage() != null && choice.getMessage().getContent() != null) {
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System.out.printf("Conversation output: %s", choice.getMessage().getContent());
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}
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}
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}
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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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```bash
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dapr run --resources-path ./components/conversation --app-id myapp --app-port 8080 --dapr-http-port 3500 --dapr-grpc-port 51439 --log-level debug -- java -jar target/dapr-java-sdk-examples-exec.jar io.dapr.examples.conversation.DemoConversationAI
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dapr run --resources-path ./components/conversation --app-id myapp --app-port 8080 --dapr-http-port 3500 --dapr-grpc-port 51439 --log-level debug -- java -jar target/dapr-java-sdk-examples-exec.jar io.dapr.examples.conversation.UserMessageDemo
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```
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<!-- END_STEP -->

‎examples/src/main/java/io/dapr/examples/conversation/ToolsCallDemo.java

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/*
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* Copyright 2021 The Dapr Authors
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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* http://www.apache.org/licenses/LICENSE-2.0
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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limitations under the License.
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*/
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package io.dapr.examples.conversation;
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import io.dapr.client.DaprClientBuilder;
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import io.dapr.client.DaprPreviewClient;
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import io.dapr.client.domain.ConversationInputAlpha2;
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import io.dapr.client.domain.ConversationMessageContent;
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import io.dapr.client.domain.ConversationRequestAlpha2;
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import io.dapr.client.domain.ConversationResponseAlpha2;
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import io.dapr.client.domain.ConversationResultAlpha2;
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import io.dapr.client.domain.ConversationResultChoices;
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import io.dapr.client.domain.ConversationTools;
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import io.dapr.client.domain.ConversationToolsFunction;
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import io.dapr.client.domain.SystemMessage;
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import io.dapr.client.domain.UserMessage;
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import reactor.core.publisher.Mono;
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import java.util.HashMap;
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import java.util.List;
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import java.util.Map;
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public class ToolsCallDemo {
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/**
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* The main method to demonstrate conversation AI with tools/function calling.
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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("Demonstrating Conversation AI with Tools/Function Calling");
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// Create system message to set context
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SystemMessage systemMessage = new SystemMessage(List.of(
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new ConversationMessageContent("You are a helpful weather assistant. Use the provided tools to get weather information.")
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));
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// Create user message asking for weather
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UserMessage userMessage = new UserMessage(List.of(
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new ConversationMessageContent("What's the weather like in San Francisco?")
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));
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// Create conversation input with messages
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ConversationInputAlpha2 conversationInput = new ConversationInputAlpha2(List.of(systemMessage, userMessage));
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// Define function parameters for the weather tool
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Map<String, Object> functionParams = new HashMap<>();
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functionParams.put("location", "string");
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functionParams.put("unit", "string");
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// Create the weather function definition
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ConversationToolsFunction weatherFunction = new ConversationToolsFunction("get_current_weather", functionParams);
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weatherFunction.setDescription("Get the current weather for a specified location");
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// Create the tool wrapper
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ConversationTools weatherTool = new ConversationTools(weatherFunction);
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// Create the conversation request with tools
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ConversationRequestAlpha2 request = new ConversationRequestAlpha2("echo", List.of(conversationInput))
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.setContextId("weather-demo-context")
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.setTemperature(0.7d)
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.setTools(List.of(weatherTool));
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// Send the request
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System.out.println("Sending request to AI with weather tool available...");
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Mono<ConversationResponseAlpha2> responseMono = client.converseAlpha2(request);
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ConversationResponseAlpha2 response = responseMono.block();
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// Process and display the response
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if (response != null && response.getOutputs() != null && !response.getOutputs().isEmpty()) {
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ConversationResultAlpha2 result = response.getOutputs().get(0);
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if (result.getChoices() != null && !result.getChoices().isEmpty()) {
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ConversationResultChoices choice = result.getChoices().get(0);
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// Check if the AI wants to call a tool
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if (choice.getMessage() != null && choice.getMessage().getToolCalls() != null) {
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System.out.println("AI requested to call tools:");
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choice.getMessage().getToolCalls().forEach(toolCall -> {
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System.out.printf("Tool: %s, Arguments: %s%n",
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toolCall.getFunction().getName(),
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toolCall.getFunction().getArguments());
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});
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}
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// Display the message content if available
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if (choice.getMessage() != null && choice.getMessage().getContent() != null) {
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System.out.printf("AI Response: %s%n", choice.getMessage().getContent());
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}
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}
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}
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System.out.println("Tools call demonstration completed.");
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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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