[fel] add key scenario cases

framework/fel/java/fel-flow/src/main/java/modelengine/fel/engine/activities/AiConditions.java

@@ -57,6 +57,23 @@ public <O> AiMatchHappen<O, D, I, RF, F> match(Operators.Whether<I> whether,
                 node -> processor.process(new AiState<>(node, this.flow())).state), this.flow());
     }
 
+    /**
+     * 指定条件和处理器创建条件分支。
+     *
+     * @param whether 表示匹配条件的 {@link Operators.Whether}{@code <}{@link I}{@code >}。
+     * @param processor 表示分支处理器的 {@link Operators.Then}{@code <}{@link O}{@code , }{@link D}{@code ,
+     * }{@link I}{@code , }{@link RF}{@code , }{@link F}{@code >}。
+     * @param <O> 表示第一个条件分支指定的返回类型。
+     * @return 表示条件分支的 {@link AiMatchHappen}{@code <}{@link O}{@code , }{@link D}{@code ,
+     * }{@link I}{@code , }{@link RF}{@code , }{@link F}{@code >}。
+     * @throws IllegalArgumentException 当 {@code processor} 为 {@code null} 时。
+     */
+    public <O> AiWhenHappen<O, D, I, RF, F> when(Operators.Whether<I> whether,
+            Operators.Then<I, O> processor) {
+        Validation.notNull(processor, "Ai branch processor cannot be null.");
+        return new AiWhenHappen<>(this.conditions.when(whether, processor), this.flow());
+    }
+
     /**
      * 指定条件和对应的处理器创建条件跳转分支。
      *

framework/fel/java/fel-flow/src/main/java/modelengine/fel/engine/activities/AiState.java

@@ -82,6 +82,18 @@ public AiState<O, D, I, RF, F> id(String id) {
         return this;
     }
 
+    /**
+     * Sets the maximum concurrency level for this state's processing pipeline.
+     *
+     * @param concurrency The maximum number of concurrent operations allowed (must be positive).
+     * @return The current state instance for method chaining.
+     * @throws IllegalArgumentException If the concurrency value is zero or negative.
+     */
+    public AiState<O, D, I, RF, F> concurrency(int concurrency) {
+        this.state.concurrency(concurrency);
+        return this;
+    }
+
     /**
      * 获取当前节点的数据订阅者。
      *

framework/fel/java/fel-flow/src/main/java/modelengine/fel/engine/activities/AiWhenHappen.java

@@ -0,0 +1,71 @@
+/*---------------------------------------------------------------------------------------------
+ *  Copyright (c) 2025 Huawei Technologies Co., Ltd. All rights reserved.
+ *  This file is a part of the ModelEngine Project.
+ *  Licensed under the MIT License. See License.txt in the project root for license information.
+ *--------------------------------------------------------------------------------------------*/
+
+package modelengine.fel.engine.activities;
+
+import modelengine.fel.engine.flows.AiFlow;
+import modelengine.fit.waterflow.domain.flow.Flow;
+import modelengine.fit.waterflow.domain.states.WhenHappen;
+import modelengine.fit.waterflow.domain.stream.operators.Operators;
+import modelengine.fitframework.inspection.Validation;
+
+/**
+ * Represents a conditional branch that matches when conditions in an AI processing flow.
+ * This class handles the branching logic when specific conditions are met in the workflow.
+ *
+ * @param <O> The output data type of the current node.
+ * @param <D> The initial data type of the containing flow.
+ * @param <I> The input parameter data type.
+ * @param <RF> The internal flow type, extending {@link Flow}{@code <D>}.
+ * @param <F> The AI flow type, extending {@link AiFlow}{@code <D, RF>}.
+ *
+ * @author 宋永坦
+ * @since 2025-06-12
+ */
+public class AiWhenHappen<O, D, I, RF extends Flow<D>, F extends AiFlow<D, RF>> {
+    private final WhenHappen<O, D, I, RF> matchHappen;
+
+    private final F flow;
+
+    /**
+     * Creates a new AI flow matching generator that handles conditional branching.
+     * This constructor initializes a stateful processor for when/then style pattern matching
+     * within AI workflows.
+     *
+     * @param matchHappen The core matching generator that evaluates conditions.
+     * @param flow The parent AI flow.
+     * @throws NullPointerException If either parameter is null.
+     */
+    public AiWhenHappen(WhenHappen<O, D, I, RF> matchHappen, F flow) {
+        this.matchHappen = Validation.notNull(matchHappen, "WhenHappen cannot be null.");
+        this.flow = Validation.notNull(flow, "Flow cannot be null.");
+    }
+
+    /**
+     * Creates a conditional branch with the specified predicate and handler.
+     *
+     * @param whether The condition predicate that determines branch activation.
+     * @param processor The transformation handler to execute when condition is met.
+     * @return A new {@link AiWhenHappen} instance representing the conditional branch.
+     * @throws IllegalArgumentException if processor is null.
+     */
+    public AiWhenHappen<O, D, I, RF, F> when(Operators.Whether<I> whether, Operators.Then<I, O> processor) {
+        Validation.notNull(processor, "Ai branch processor cannot be null.");
+        return new AiWhenHappen<>(this.matchHappen.when(whether, processor), this.flow);
+    }
+
+    /**
+     * Provides a default processing logic and terminates the conditional node.
+     *
+     * @param processor The handler to process unmatched inputs.
+     * @return An {@link AiState} representing the terminal node of the conditional flow.
+     * @throws IllegalArgumentException if processor is null.
+     */
+    public AiState<O, D, O, RF, F> others(Operators.Then<I, O> processor) {
+        Validation.notNull(processor, "Ai branch processor cannot be null.");
+        return new AiState<>(this.matchHappen.others(processor), this.flow);
+    }
+}

framework/fel/java/fel-flow/src/main/java/modelengine/fel/engine/flows/Conversation.java

@@ -47,6 +47,9 @@ public class Conversation<D, R> {
      */
     public Conversation(AiProcessFlow<D, R> flow, FlowSession session) {
         this.flow = Validation.notNull(flow, "Flow cannot be null.");
+        if (session != null) {
+            session.begin();
+        }
         this.session =
                 (session == null) ? this.setConverseListener(new FlowSession(true)) : this.setSubConverseListener(session);
         this.session.begin();

framework/fel/java/fel-flow/src/main/java/modelengine/fel/engine/operators/patterns/AbstractFlowPattern.java

@@ -89,7 +89,7 @@ public FlowEmitter<O> invoke(I data) {
     public Pattern<I, O> sync() {
         return new SimplePattern<>(data -> {
             FlowSession require = AiFlowSession.require();
-            FlowSession session = new FlowSession(true);
+            FlowSession session = new FlowSession(require.preserved());
             Window window = session.begin();
             session.copySessionState(require);
             ConverseLatch<O> conversation = this.getFlow().converse(session).offer(data);
@@ -116,7 +116,7 @@ public Flow<I> origin() {
      */
     protected static <O> FlowSession buildFlowSession(FlowEmitter<O> emitter) {
         FlowSession mainSession = AiFlowSession.require();
-        FlowSession flowSession = FlowSession.newRootSession(mainSession, true);
+        FlowSession flowSession = FlowSession.newRootSession(mainSession, mainSession.preserved());
         flowSession.setInnerState(PARENT_SESSION_ID_KEY, mainSession.getId());
         ResultAction<O> resultAction = emitter::emit;
         flowSession.setInnerState(RESULT_ACTION_KEY, resultAction);

framework/fel/java/fel-flow/src/test/java/modelengine/fel/engine/AiFlowCaseTest.java

@@ -0,0 +1,226 @@
+/*---------------------------------------------------------------------------------------------
+ *  Copyright (c) 2025 Huawei Technologies Co., Ltd. All rights reserved.
+ *  This file is a part of the ModelEngine Project.
+ *  Licensed under the MIT License. See License.txt in the project root for license information.
+ *--------------------------------------------------------------------------------------------*/
+
+package modelengine.fel.engine;
+
+import modelengine.fel.core.chat.ChatMessage;
+import modelengine.fel.core.chat.ChatOption;
+import modelengine.fel.core.chat.support.AiMessage;
+import modelengine.fel.core.util.Tip;
+import modelengine.fel.engine.flows.AiFlows;
+import modelengine.fel.engine.flows.AiProcessFlow;
+import modelengine.fel.engine.flows.ConverseLatch;
+import modelengine.fel.engine.operators.models.ChatFlowModel;
+import modelengine.fel.engine.operators.prompts.Prompts;
+import modelengine.fit.waterflow.domain.context.FlowSession;
+import modelengine.fit.waterflow.domain.context.StateContext;
+import modelengine.fit.waterflow.domain.utils.SleepUtil;
+import modelengine.fitframework.flowable.Choir;
+
+import org.junit.jupiter.api.Assertions;
+import org.junit.jupiter.api.DisplayName;
+import org.junit.jupiter.api.Nested;
+import org.junit.jupiter.api.Test;
+
+import java.util.concurrent.atomic.AtomicInteger;
+
+/**
+ * Test cases demonstrating different flow control scenarios in AI processing pipelines.
+ * Contains nested test classes for specific flow control mechanisms.
+ *
+ * @author 宋永坦
+ * @since 2025-06-11
+ */
+public class AiFlowCaseTest {
+    private static final int SPEED = 1;
+
+    @Nested
+    class DesensitizeCase {
+        private final ChatFlowModel model = new ChatFlowModel((prompt, chatOption) -> Choir.create(emitter -> {
+            emitter.emit(new AiMessage("<think>"));
+            int takeTime = 10 * SPEED;
+            SleepUtil.sleep(takeTime);
+            for (int i = 0; i < 48; i++) {
+                emitter.emit(new AiMessage(String.valueOf(i)));
+                SleepUtil.sleep(takeTime);
+            }
+            emitter.emit(new AiMessage("</think>"));
+            SleepUtil.sleep(takeTime);
+            for (int i = 100; i < 150; i++) {
+                emitter.emit(new AiMessage(String.valueOf(i)));
+                SleepUtil.sleep(takeTime);
+            }
+            emitter.complete();
+        }), ChatOption.custom().model("modelName").stream(true).build());
+
+        private final AiProcessFlow<Tip, String> flow = AiFlows.<Tip>create()
+                .prompt(Prompts.human("{{0}}"))
+                .generate(model)
+                .map(this::classic)
+                .conditions()
+                .when(chunk -> chunk.isThinkContent, input -> input)
+                .others(input -> {
+                    this.log(input);
+                    return input;
+                })
+                .map(this::mockDesensitize1)
+                .map(this::mockDesensitize2)
+                .close();
+
+        @Test
+        @DisplayName("DesensitizeCase")
+        void run() {
+            AtomicInteger counter = new AtomicInteger(0);
+            long startTime = System.currentTimeMillis();
+            System.out.printf("time:%s, start.\n", startTime);
+            ConverseLatch<String> result = flow.converse(new FlowSession(true)).doOnConsume(answer -> {
+                System.out.printf("time:%s, chunk=%s\n", System.currentTimeMillis(), answer);
+                counter.incrementAndGet();
+            }).offer(Tip.fromArray("hi"));
+            result.await();
+            System.out.printf("time:%s, cost=%s\n", System.currentTimeMillis(), System.currentTimeMillis() - startTime);
+            Assertions.assertEquals(100, counter.get());
+        }
+
+        private Chunk classic(ChatMessage message, StateContext ctx) {
+            if (message.text().trim().equals("<think>")) {
+                ctx.setState("isThinking", true);
+                return new Chunk(true, message.text());
+            }
+            if (message.text().trim().equals("</think>")) {
+                ctx.setState("isThinking", false);
+                return new Chunk(true, message.text());
+            }
+            if (Boolean.TRUE.equals(ctx.getState("isThinking"))) {
+                return new Chunk(true, message.text());
+            }
+            return new Chunk(false, message.text());
+        }
+
+        private String mockDesensitize1(Chunk chunk) {
+            SleepUtil.sleep(10 * SPEED);
+            return chunk.content.replace("3", "*");
+        }
+
+        private String mockDesensitize2(String chunk) {
+            SleepUtil.sleep(10 * SPEED);
+            return chunk.replace("4", "*");
+        }
+
+        private void log(Chunk chunk) {
+            System.out.println("log content:" + chunk.content);
+        }
+
+        private static class Chunk {
+            private final boolean isThinkContent;
+            private final String content;
+
+            private Chunk(boolean isThinkContent, String content) {this.isThinkContent = isThinkContent;
+                this.content = content;
+            }
+        }
+    }
+
+    /**
+     * Simulates a backpressure scenario where:
+     * <ol>
+     *     <li>The LLM generates data faster than the TTS can process it.</li>
+     *     <li>TTS processing is constrained to a single thread.</li>
+     *     <li>TTS processing speed is artificially slowed.</li>
+     * </ol>
+     */
+    @Nested
+    class BackPressureCase {
+        private final ChatFlowModel model = new ChatFlowModel((prompt, chatOption) -> Choir.create(emitter -> {
+            for (int i = 0; i < 100; i++) {
+                emitter.emit(new AiMessage(String.valueOf(i)));
+                SleepUtil.sleep(5 * SPEED);
+            }
+            emitter.complete();
+            System.out.printf("time:%s, generate completed.\n", System.currentTimeMillis());
+        }), ChatOption.custom().model("modelName").stream(true).build());
+
+        private final AiProcessFlow<Tip, String> flow = AiFlows.<Tip>create()
+                .prompt(Prompts.human("{{0}}"))
+                .generate(model)
+                .map(this::mockDesensitize).concurrency(1) // Limit processing to 1 concurrent thread
+                .map(this::mockTTS).concurrency(1) // Limit processing to 1 concurrent thread
+                .close();
+
+        @Test
+        @DisplayName("BackPressureCase")
+        void run() {
+            AtomicInteger counter = new AtomicInteger(0);
+            long startTime = System.currentTimeMillis();
+            System.out.printf("time:%s, start.\n", startTime);
+            ConverseLatch<String> result = flow.converse(new FlowSession(false)).doOnConsume(answer -> {
+                System.out.printf("time:%s, chunk=%s\n", System.currentTimeMillis(), answer);
+                counter.incrementAndGet();
+            }).offer(Tip.fromArray("hi"));
+            result.await();
+            System.out.printf("time:%s, cost=%s\n", System.currentTimeMillis(), System.currentTimeMillis() - startTime);
+            Assertions.assertEquals(100, counter.get());
+        }
+
+        private String mockDesensitize(ChatMessage chunk) {
+            // Simulate time-consuming operation with a delay.
+            SleepUtil.sleep(10 * SPEED);
+            return chunk.text().replace("3", "*");
+        }
+
+        private String mockTTS(String chunk) {
+            // Simulate time-consuming operation with a delay.
+            SleepUtil.sleep(10 * SPEED);
+            return chunk;
+        }
+    }
+
+    /**
+     * Demonstrates concurrent processing with balanced throughput where:
+     * <ol>
+     *     <li>LLM generates data at moderate pace.</li>
+     *     <li>Downstream processing runs with 3 concurrent threads.</li>
+     *     <li>Processing speed is slightly slower than generation (3 : 1).</li>
+     * </ol>
+     */
+    @Nested
+    class ConcurrencyCase {
+        private final ChatFlowModel model = new ChatFlowModel((prompt, chatOption) -> Choir.create(emitter -> {
+            for (int i = 0; i < 100; i++) {
+                emitter.emit(new AiMessage(String.valueOf(i)));
+                SleepUtil.sleep(10 * SPEED);
+            }
+            emitter.complete();
+        }), ChatOption.custom().model("modelName").stream(true).build());
+
+        private final AiProcessFlow<Tip, String> flow = AiFlows.<Tip>create()
+                .prompt(Prompts.human("{{0}}"))
+                .generate(model)
+                .map(this::mockDesensitize).concurrency(3) // Set processing to 3 concurrent thread
+                .close();
+
+        @Test
+        @DisplayName("ConcurrencyCase")
+        void run() {
+            AtomicInteger counter = new AtomicInteger(0);
+            long startTime = System.currentTimeMillis();
+            System.out.printf("time:%s, start.\n", startTime);
+            ConverseLatch<String> result = flow.converse(new FlowSession(false)).doOnConsume(answer -> {
+                System.out.printf("time:%s, chunk=%s\n", System.currentTimeMillis(), answer);
+                counter.incrementAndGet();
+            }).offer(Tip.fromArray("hi"));
+            result.await();
+            System.out.printf("time:%s, cost=%s\n", System.currentTimeMillis(), System.currentTimeMillis() - startTime);
+            Assertions.assertEquals(100, counter.get());
+        }
+
+        private String mockDesensitize(ChatMessage chunk) {
+            // Simulate slower processing at 1/3 speed of LLM generation.
+            SleepUtil.sleep(30 * SPEED);
+            return chunk.text().replace("3", "*");
+        }
+    }
+}

framework/waterflow/java/waterflow-core/src/main/java/modelengine/fit/waterflow/domain/context/repo/flowcontext/FlowContextMessenger.java

@@ -54,4 +54,18 @@ default <I> void send(ProcessType type, Subscriber<I, ?> subscriber, List<FlowCo
      * @param <I> 流程实例执行时的入参数据类型，用于泛型推倒
      */
     <I> void sendCallback(List<FlowContext<I>> contexts);
+
+    /**
+     * Directly processes a list of flow contexts through the specified subscriber.
+     * This method serves as a default implementation for immediate processing without
+     * any intermediate transformations or routing.
+     *
+     * @param <I> The type of input data contained in the flow contexts.
+     * @param type The type of processing to be performed.
+     * @param subscriber The subscriber that will handle the processing.
+     * @param context List of flow contexts to be processed.
+     */
+    default <I> void directProcess(ProcessType type, Subscriber<I, ?> subscriber, List<FlowContext<I>> context) {
+        subscriber.process(type, context);
+    }
 }