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Add PythonChatModel Example in e2e test
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‎e2e-test/integration-test/pom.xml‎

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<artifactId>flink-agents-integrations-embedding-models-ollama</artifactId>
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<version>${project.version}</version>
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</dependency>
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<dependency>
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<groupId>org.apache.flink</groupId>
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<artifactId>flink-python</artifactId>
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<version>${flink.version}</version>
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</dependency>
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</dependencies>
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</project>

‎e2e-test/integration-test/src/main/java/org/apache/flink/agents/integration/test/AgentWithPythonChatModel.java‎

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/*
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* Licensed to the Apache Software Foundation (ASF) under one
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* or more contributor license agreements. See the NOTICE file
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* distributed with this work for additional information
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* regarding copyright ownership. The ASF licenses this file
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* to you under the Apache License, Version 2.0 (the
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* "License"); you may not use this file except in compliance
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* with the License. You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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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 org.apache.flink.agents.integration.test;
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import org.apache.flink.agents.api.Agent;
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import org.apache.flink.agents.api.InputEvent;
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import org.apache.flink.agents.api.OutputEvent;
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import org.apache.flink.agents.api.annotation.Action;
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import org.apache.flink.agents.api.annotation.ChatModelConnection;
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import org.apache.flink.agents.api.annotation.ChatModelSetup;
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import org.apache.flink.agents.api.annotation.Tool;
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import org.apache.flink.agents.api.annotation.ToolParam;
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import org.apache.flink.agents.api.chat.messages.ChatMessage;
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import org.apache.flink.agents.api.chat.messages.MessageRole;
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import org.apache.flink.agents.api.context.RunnerContext;
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import org.apache.flink.agents.api.event.ChatRequestEvent;
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import org.apache.flink.agents.api.event.ChatResponseEvent;
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import org.apache.flink.agents.api.resource.ResourceDescriptor;
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import org.apache.flink.agents.api.resource.ResourceType;
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import org.apache.flink.agents.api.resource.python.PythonChatModelConnection;
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import org.apache.flink.agents.api.resource.python.PythonChatModelSetup;
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import java.util.Collections;
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import java.util.List;
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/**
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* Agent example integrating a built-in Python chat model into Flink Agents.
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*
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* <p>This class demonstrates how to:
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*
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* <ul>
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* <li>Declare a chat model connection using {@link ChatModelConnection} metadata pointing to
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* {@link PythonChatModelConnection}
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* <li>Declare a chat model setup using {@link ChatModelSetup} metadata pointing to {@link
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* PythonChatModelSetup}
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* <li>Expose callable tools via {@link Tool} annotated static methods (temperature conversion,
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* BMI, random number)
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* <li>Fetch a chat model from the {@link RunnerContext} and perform a single-turn chat
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* <li>Emit the model response as an {@link OutputEvent}
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* </ul>
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*
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* <p>The {@code pythonChatModel()} method publishes a resource with type {@link
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* ResourceType#CHAT_MODEL} so it can be retrieved at runtime inside the {@code process} action. The
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* resource is configured with the connection name, the model name and the list of tool names that
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* the model is allowed to call.
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*/
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public class AgentWithPythonChatModel extends Agent {
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@ChatModelConnection
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public static ResourceDescriptor pythonChatModelConnection() {
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return ResourceDescriptor.Builder.newBuilder(PythonChatModelConnection.class.getName())
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.addInitialArgument(
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"module", "flink_agents.integrations.chat_models.tongyi_chat_model")
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.addInitialArgument("clazz", "TongyiChatModelConnection")
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.build();
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}
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@ChatModelSetup
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public static ResourceDescriptor pythonChatModel() {
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return ResourceDescriptor.Builder.newBuilder(PythonChatModelSetup.class.getName())
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.addInitialArgument("connection", "pythonChatModelConnection")
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.addInitialArgument(
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"module", "flink_agents.integrations.chat_models.tongyi_chat_model")
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.addInitialArgument("clazz", "TongyiChatModelSetup")
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.addInitialArgument("model", "qwen-plus")
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.addInitialArgument(
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"tools",
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List.of("calculateBMI", "convertTemperature", "createRandomNumber"))
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.addInitialArgument("extract_reasoning", "true")
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.build();
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}
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@Tool(description = "Converts temperature between Celsius and Fahrenheit")
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public static double convertTemperature(
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@ToolParam(name = "value", description = "Temperature value to convert") Double value,
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@ToolParam(
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name = "fromUnit",
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description = "Source unit ('C' for Celsius or 'F' for Fahrenheit)")
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String fromUnit,
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@ToolParam(
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name = "toUnit",
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description = "Target unit ('C' for Celsius or 'F' for Fahrenheit)")
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String toUnit) {
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fromUnit = fromUnit.toUpperCase();
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toUnit = toUnit.toUpperCase();
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if (fromUnit.equals(toUnit)) {
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return value;
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}
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if (fromUnit.equals("C") && toUnit.equals("F")) {
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return (value * 9 / 5) + 32;
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} else if (fromUnit.equals("F") && toUnit.equals("C")) {
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return (value - 32) * 5 / 9;
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} else {
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throw new IllegalArgumentException("Invalid temperature units. Use 'C' or 'F'");
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}
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}
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@Tool(description = "Calculates Body Mass Index (BMI)")
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public static double calculateBMI(
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@ToolParam(name = "weightKg", description = "Weight in kilograms") Double weightKg,
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@ToolParam(name = "heightM", description = "Height in meters") Double heightM) {
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if (weightKg <= 0 || heightM <= 0) {
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throw new IllegalArgumentException("Weight and height must be positive values");
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}
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return weightKg / (heightM * heightM);
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}
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@Tool(description = "Create a random number")
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public static double createRandomNumber() {
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return Math.random();
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}
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@Action(listenEvents = {InputEvent.class})
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public static void process(InputEvent event, RunnerContext ctx) throws Exception {
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ctx.sendEvent(
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new ChatRequestEvent(
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"pythonChatModel",
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Collections.singletonList(
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new ChatMessage(MessageRole.USER, (String) event.getInput()))));
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}
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@Action(listenEvents = {ChatResponseEvent.class})
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public static void processChatResponse(ChatResponseEvent event, RunnerContext ctx) {
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ctx.sendEvent(new OutputEvent(event.getResponse().getContent()));
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}
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}

‎e2e-test/integration-test/src/main/java/org/apache/flink/agents/integration/test/AgentWithPythonChatModelExample.java‎

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/*
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* Licensed to the Apache Software Foundation (ASF) under one
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* or more contributor license agreements. See the NOTICE file
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* distributed with this work for additional information
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* regarding copyright ownership. The ASF licenses this file
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* to you under the Apache License, Version 2.0 (the
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* "License"); you may not use this file except in compliance
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* with the License. You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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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 org.apache.flink.agents.integration.test;
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import org.apache.flink.agents.api.AgentsExecutionEnvironment;
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import org.apache.flink.api.java.functions.KeySelector;
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import org.apache.flink.streaming.api.datastream.DataStream;
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import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
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/**
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* Example application that applies {@link AgentWithPythonChatModel} to a DataStream of user
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* prompts.
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*/
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public class AgentWIthPythonChatModelExample {
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/** Runs the example pipeline. */
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public static void main(String[] args) throws Exception {
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// Create the execution environment
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StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
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env.setParallelism(1);
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// Use prompts that trigger different tool calls in the agent
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DataStream<String> inputStream =
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env.fromData(
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"Convert 25 degrees Celsius to Fahrenheit",
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"What is 98.6 Fahrenheit in Celsius?",
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"Change 32 degrees Celsius to Fahrenheit",
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"If it's 75 degrees Fahrenheit, what would that be in Celsius?",
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"Convert room temperature of 20C to F",
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"Calculate BMI for someone who is 1.75 meters tall and weighs 70 kg",
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"What's the BMI for a person weighing 85 kg with height 1.80 meters?",
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"Can you tell me the BMI if I'm 1.65m tall and weigh 60kg?",
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"Find BMI for 75kg weight and 1.78m height",
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"Create me a random number please");
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// Create agents execution environment
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AgentsExecutionEnvironment agentsEnv =
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AgentsExecutionEnvironment.getExecutionEnvironment(env);
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// Apply agent to the DataStream and use the prompt itself as the key
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DataStream<Object> outputStream =
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agentsEnv
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.fromDataStream(inputStream, (KeySelector<String, String>) value -> value)
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.apply(new AgentWithPythonChatModel())
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.toDataStream();
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// Print the results
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outputStream.print();
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// Execute the pipeline
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agentsEnv.execute();
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}
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}

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