refactor: clarify agent pattern names

- Remove redundant workflow suffix from agentic pattern names and related classes
- Update documentation to reflect pattern name changes

agentic-patterns/README.md

@@ -55,8 +55,8 @@ Implements a classification system that directs input to specialized followup ta
 - Content moderation systems
 - Query optimization based on complexity
 
-### 4. Orchestrator-Workers Workflow
-[orchestrator-workers-workflow/](orchestrator-workers-workflow/)
+### 4. Orchestrator-Workers
+[orchestrator-workers/](orchestrator-workers/)
 
 Implements a flexible system where a central LLM orchestrates task decomposition and delegates to specialized worker LLMs.
 
@@ -70,8 +70,8 @@ Implements a flexible system where a central LLM orchestrates task decomposition
 - Multi-source research tasks
 - Adaptive content creation
 
-### 5. Evaluator-Optimizer Workflow
-[evaluator-optimizer-workflow/](evaluator-optimizer-workflow/)
+### 5. Evaluator-Optimizer
+[evaluator-optimizer/](evaluator-optimizer/)
 
 Implements an iterative refinement process where one LLM generates solutions while another provides evaluation and feedback.
 

agentic-patterns/evaluator-optimizer/README.md

@@ -1,8 +1,8 @@
-# Evaluator-Optimizer Workflow Pattern
+# Evaluator-Optimizer Pattern
 
-This project demonstrates the Evaluator-Optimizer workflow pattern for building effective LLM-based systems, as described in [Anthropic's research on building effective agents](https://www.anthropic.com/research/building-effective-agents).
+This project demonstrates the Evaluator-Optimizer pattern for building effective LLM-based systems, as described in [Anthropic's research on building effective agents](https://www.anthropic.com/research/building-effective-agents).
 
-![Evaluator-Optimizer Workflow](https://www.anthropic.com/_next/image?url=https%3A%2F%2Fwww-cdn.anthropic.com%2Fimages%2F4zrzovbb%2Fwebsite%2F14f51e6406ccb29e695da48b17017e899a6119c7-2401x1000.png&w=3840&q=75)
+![Evaluator-Optimizer](https://www.anthropic.com/_next/image?url=https%3A%2F%2Fwww-cdn.anthropic.com%2Fimages%2F4zrzovbb%2Fwebsite%2F14f51e6406ccb29e695da48b17017e899a6119c7-2401x1000.png&w=3840&q=75)
 
 ## Overview
 
@@ -48,7 +48,7 @@ This pattern is particularly effective when:
 The implementation uses Spring AI's ChatClient for LLM interactions and consists of:
 
 ```java
-public class EvaluatorOptimizerWorkflow {
+public class EvaluatorOptimizer {
     public RefinedResponse loop(String task) {
         // 1. Generate initial solution
         Generation generation = generate(task, context);
@@ -68,10 +68,10 @@ public class EvaluatorOptimizerWorkflow {
 
 ```java
 ChatClient chatClient = // ... initialize chat client
-EvaluatorOptimizerWorkflow workflow = new EvaluatorOptimizerWorkflow(chatClient);
+EvaluatorOptimizer agent = new EvaluatorOptimizer(chatClient);
 
 // Process a task
-RefinedResponse response = workflow.loop(
+RefinedResponse response = agent.loop(
     "Create a Java class implementing a thread-safe counter"
 );
 
@@ -82,11 +82,11 @@ System.out.println("Evolution: " + response.chainOfThought());
 
 ## Customization
 
-The workflow can be customized through:
+The pattern can be customized through:
 
 1. **Custom Prompts**: Provide specialized prompts for generator and evaluator
 ```java
-workflow = new EvaluatorOptimizerWorkflow(
+agent = new EvaluatorOptimizer(
     chatClient,
     customGeneratorPrompt,
     customEvaluatorPrompt

agentic-patterns/evaluator-optimizer/pom.xml

@@ -10,9 +10,9 @@
 		<relativePath /> <!-- lookup parent from repository -->
 	</parent>
 	<groupId>com.example.spring.ai</groupId>
-	<artifactId>evaluator-optimizer-workflow</artifactId>
+	<artifactId>evaluator-optimizer</artifactId>
 	<version>0.0.1-SNAPSHOT</version>
-	<name>evaluator-optimizer-workflow</name>
+	<name>evaluator-optimizer</name>
 	<description>Demo project for Spring Boot</description>
 	<properties>
 		<java.version>17</java.version>
@@ -25,10 +25,10 @@
 		</dependency>
 
 
-		<!-- <dependency>
+		<dependency>
 			<groupId>org.springframework.ai</groupId>
 			<artifactId>spring-ai-openai-spring-boot-starter</artifactId>
-		</dependency> -->
+		</dependency>
 
 		<!-- <dependency>
 			<groupId>org.springframework.ai</groupId>
@@ -36,10 +36,10 @@
 		</dependency> -->
 
 
-		<dependency>
+		<!-- <dependency>
 			<groupId>org.springframework.ai</groupId>
 			<artifactId>spring-ai-ollama-spring-boot-starter</artifactId>
-		</dependency>
+		</dependency> -->
 
 		<dependency>
 			<groupId>org.springframework.boot</groupId>

agentic-patterns/evaluator-optimizer/src/main/java/com/example/agentic/Application.java

@@ -16,7 +16,7 @@
 */
 package com.example.agentic;
 
-import com.example.agentic.EvaluatorOptimizerWorkflow.RefinedResponse;
+import com.example.agentic.EvaluatorOptimizer.RefinedResponse;
 
 import org.springframework.ai.chat.client.ChatClient;
 import org.springframework.boot.CommandLineRunner;
@@ -25,7 +25,7 @@ import org.springframework.boot.autoconfigure.SpringBootApplication;
 import org.springframework.context.annotation.Bean;
 
 // ------------------------------------------------------------
-// EVALUATION WORKFLOW
+// EVALUATOR-OPTIMIZER
 // ------------------------------------------------------------
 
 @SpringBootApplication
@@ -39,7 +39,7 @@ public class Application {
 	public CommandLineRunner commandLineRunner(ChatClient.Builder chatClientBuilder) {
 		var chatClient = chatClientBuilder.build();
 		return args -> {
-			RefinedResponse refinedResponse = new EvaluatorOptimizerWorkflow(chatClient).loop("""
+			RefinedResponse refinedResponse = new EvaluatorOptimizer(chatClient).loop("""
 					<user input>
 					Implement a Stack in Java with:
 					1. push(x)
@@ -47,7 +47,6 @@ public class Application {
 					3. getMin()
 					All operations should be O(1).
 					All inner fields should be private and when used should be prefixed with 'this.'.
-					Add inline code documentation.
 					</user input>
 					""");
 

agentic-patterns/evaluator-optimizer/src/main/java/com/example/agentic/EvaluatorOptimizer.java

@@ -74,7 +74,7 @@ import org.springframework.util.Assert;
  *      effective agents</a>
  */
 @SuppressWarnings("null")
-public class EvaluatorOptimizerWorkflow {
+public class EvaluatorOptimizer {
 
 	public static final String DEFAULT_GENERATOR_PROMPT = """
 			Your goal is to complete the task based on the input. If there are feedback
@@ -101,6 +101,7 @@ public class EvaluatorOptimizerWorkflow {
 
 	public static final String DEFAULT_EVALUATOR_PROMPT = """
 			Evaluate this code implementation for correctness, time complexity, and best practices.
+			Ensure the code have proper javadoc documentation.
 			Respond with EXACTLY this JSON format on a single line:
 
 			{"evaluation":"PASS, NEEDS_IMPROVEMENT, or FAIL", "feedback":"Your feedback here"}
@@ -150,11 +151,11 @@ public class EvaluatorOptimizerWorkflow {
 
 	private final String evaluatorPrompt;
 
-	public EvaluatorOptimizerWorkflow(ChatClient chatClient) {
+	public EvaluatorOptimizer(ChatClient chatClient) {
 		this(chatClient, DEFAULT_GENERATOR_PROMPT, DEFAULT_EVALUATOR_PROMPT);
 	}
 
-	public EvaluatorOptimizerWorkflow(ChatClient chatClient, String generatorPrompt, String evaluatorPrompt) {
+	public EvaluatorOptimizer(ChatClient chatClient, String generatorPrompt, String evaluatorPrompt) {
 		Assert.notNull(chatClient, "ChatClient must not be null");
 		Assert.hasText(generatorPrompt, "Generator prompt must not be empty");
 		Assert.hasText(evaluatorPrompt, "Evaluator prompt must not be empty");

agentic-patterns/orchestrator-workers/README.md

@@ -27,7 +27,7 @@ This pattern is particularly effective for:
 The implementation uses Spring AI's ChatClient for LLM interactions and consists of:
 
 ```java
-public class OrchestratorWorkersWorkflow {
+public class OrchestratorWorkers {
     public WorkerResponse process(String taskDescription) {
         // 1. Orchestrator analyzes task and determines subtasks
         OrchestratorResponse orchestratorResponse = // ...
@@ -45,10 +45,10 @@ public class OrchestratorWorkersWorkflow {
 
 ```java
 ChatClient chatClient = // ... initialize chat client
-OrchestratorWorkersWorkflow workflow = new OrchestratorWorkersWorkflow(chatClient);
+OrchestratorWorkers agent = new OrchestratorWorkers(chatClient);
 
 // Process a task
-WorkerResponse response = workflow.process(
+WorkerResponse response = agent.process(
     "Generate both technical and user-friendly documentation for a REST API endpoint"
 );
 
@@ -59,11 +59,11 @@ System.out.println("Worker Outputs: " + response.workerResponses());
 
 ## Customization
 
-The workflow can be customized through:
+The pattern can be customized through:
 
 1. **Custom Prompts**: Provide specialized prompts for orchestrator and workers
 ```java
-workflow = new OrchestratorWorkersWorkflow(
+agent = new OrchestratorWorkers(
     chatClient,
     customOrchestratorPrompt,
     customWorkerPrompt

agentic-patterns/orchestrator-workers/pom.xml

@@ -10,9 +10,9 @@
 		<relativePath /> <!-- lookup parent from repository -->
 	</parent>
 	<groupId>com.example.spring.ai</groupId>
-	<artifactId>orchestrator-workers-workflow</artifactId>
+	<artifactId>orchestrator-workers</artifactId>
 	<version>0.0.1-SNAPSHOT</version>
-	<name>orchestrator-workers-workflow</name>
+	<name>orchestrator-workers</name>
 	<description>Demo project for Spring Boot</description>
 	<properties>
 		<java.version>17</java.version>

agentic-patterns/orchestrator-workers/src/main/java/com/example/agentic/Application.java

@@ -23,7 +23,7 @@ import org.springframework.boot.autoconfigure.SpringBootApplication;
 import org.springframework.context.annotation.Bean;
 
 // ------------------------------------------------------------
-// ORCHESTRATOR WORKFLOW
+// ORCHESTRATOR WORKERS
 // ------------------------------------------------------------
 
 @SpringBootApplication
@@ -38,7 +38,7 @@ public class Application {
 		var chatClient = chatClientBuilder.build();
 		return args -> {
 
-			new OrchestratorWorkersWorkflow(chatClient)
+			new OrchestratorWorkers(chatClient)
 					.process("Write a product description for a new eco-friendly water bottle");
 
 		};

agentic-patterns/orchestrator-workers/src/main/java/com/example/agentic/OrchestratorWorkers.java

@@ -21,9 +21,9 @@ import org.springframework.ai.chat.client.ChatClient;
 import org.springframework.util.Assert;
 
 /**
- * Workflow: <b>Orchestrator-workers</b>
+ * Pattern: <b>Orchestrator-workers</b>
  * <p/>
- * In this workflow, a central LLM (the orchestrator) dynamically breaks down
+ * In this pattern, a central LLM (the orchestrator) dynamically breaks down
  * complex tasks into subtasks,
  * delegates them to worker LLMs, and uses a synthesizer to combine their
  * results. The orchestrator analyzes
@@ -41,7 +41,7 @@ import org.springframework.util.Assert;
  * result</li>
  * </ul>
  * <p/>
- * When to use: This workflow is well-suited for complex tasks where you can't
+ * When to use: This pattern is well-suited for complex tasks where you can't
  * predict the subtasks needed upfront.
  * For example:
  * <ul>
@@ -64,7 +64,7 @@ import org.springframework.util.Assert;
  *      "https://www.anthropic.com/research/building-effective-agents">Building
  *      effective agents</a>
  */
-public class OrchestratorWorkersWorkflow {
+public class OrchestratorWorkers {
 
 	private final ChatClient chatClient;
 	private final String orchestratorPrompt;
@@ -135,22 +135,22 @@ public class OrchestratorWorkersWorkflow {
 	}
 
 	/**
-	 * Creates a new OrchestratorWorkersWorkflow with default prompts.
+	 * Creates a new OrchestratorWorkers with default prompts.
 	 * 
 	 * @param chatClient The ChatClient to use for LLM interactions
 	 */
-	public OrchestratorWorkersWorkflow(ChatClient chatClient) {
+	public OrchestratorWorkers(ChatClient chatClient) {
 		this(chatClient, DEFAULT_ORCHESTRATOR_PROMPT, DEFAULT_WORKER_PROMPT);
 	}
 
 	/**
-	 * Creates a new OrchestratorWorkersWorkflow with custom prompts.
+	 * Creates a new OrchestratorWorkers with custom prompts.
 	 * 
 	 * @param chatClient         The ChatClient to use for LLM interactions
 	 * @param orchestratorPrompt Custom prompt for the orchestrator LLM
 	 * @param workerPrompt       Custom prompt for the worker LLMs
 	 */
-	public OrchestratorWorkersWorkflow(ChatClient chatClient, String orchestratorPrompt, String workerPrompt) {
+	public OrchestratorWorkers(ChatClient chatClient, String orchestratorPrompt, String workerPrompt) {
 		Assert.notNull(chatClient, "ChatClient must not be null");
 		Assert.hasText(orchestratorPrompt, "Orchestrator prompt must not be empty");
 		Assert.hasText(workerPrompt, "Worker prompt must not be empty");
@@ -161,7 +161,7 @@ public class OrchestratorWorkersWorkflow {
 	}
 
 	/**
-	 * Processes a task using the orchestrator-workers workflow pattern.
+	 * Processes a task using the orchestrator-workers pattern.
 	 * First, the orchestrator analyzes the task and breaks it down into subtasks.
 	 * Then, workers execute each subtask in parallel.
 	 * Finally, the results are combined into a single response.

agentic-patterns/pom.xml

@@ -17,8 +17,8 @@
 		<module>chain-workflow</module>
 		<module>parallelization-worflow</module>
 		<module>routing-workflow</module>
-		<module>orchestrator-workers-workflow</module>
-		<module>evaluator-optimizer-workflow</module>
+		<module>orchestrator-workers</module>
+		<module>evaluator-optimizer</module>
 	</modules>