refactor(action): remove problematic action tendency cache

Partner-Core/src/main/java/work/slhaf/partner/core/action/ActionCapability.java

@@ -6,7 +6,6 @@ import work.slhaf.partner.api.agent.factory.capability.annotation.Capability;
 import work.slhaf.partner.core.action.entity.ExecutableAction;
 import work.slhaf.partner.core.action.entity.MetaAction;
 import work.slhaf.partner.core.action.entity.MetaActionInfo;
-import work.slhaf.partner.core.action.entity.cache.CacheAdjustData;
 import work.slhaf.partner.core.action.entity.intervention.MetaIntervention;
 import work.slhaf.partner.core.action.runner.RunnerClient;
 
@@ -22,10 +21,6 @@ public interface ActionCapability {
 
     Set<ExecutableAction> listActions(@Nullable ExecutableAction.Status status, @Nullable String source);
 
-    List<String> selectTendencyCache(String input);
-
-    void updateTendencyCache(CacheAdjustData data);
-
     ExecutorService getExecutor(ActionCore.ExecutorType type);
 
     MetaAction loadMetaAction(@NonNull String actionKey);

Partner-Core/src/main/java/work/slhaf/partner/core/action/ActionCore.java

@@ -6,14 +6,10 @@ import lombok.val;
 import org.jetbrains.annotations.Nullable;
 import work.slhaf.partner.api.agent.factory.capability.annotation.CapabilityCore;
 import work.slhaf.partner.api.agent.factory.capability.annotation.CapabilityMethod;
-import work.slhaf.partner.common.vector.VectorClient;
 import work.slhaf.partner.core.PartnerCore;
 import work.slhaf.partner.core.action.entity.ExecutableAction;
 import work.slhaf.partner.core.action.entity.MetaAction;
 import work.slhaf.partner.core.action.entity.MetaActionInfo;
-import work.slhaf.partner.core.action.entity.cache.ActionCacheData;
-import work.slhaf.partner.core.action.entity.cache.CacheAdjustData;
-import work.slhaf.partner.core.action.entity.cache.CacheAdjustMetaData;
 import work.slhaf.partner.core.action.entity.intervention.InterventionType;
 import work.slhaf.partner.core.action.entity.intervention.MetaIntervention;
 import work.slhaf.partner.core.action.exception.MetaActionNotFoundException;
@@ -26,8 +22,6 @@ import java.util.concurrent.ConcurrentHashMap;
 import java.util.concurrent.CopyOnWriteArraySet;
 import java.util.concurrent.ExecutorService;
 import java.util.concurrent.Executors;
-import java.util.concurrent.locks.Lock;
-import java.util.concurrent.locks.ReentrantLock;
 import java.util.stream.Collectors;
 
 @SuppressWarnings("FieldMayBeFinal")
@@ -37,11 +31,10 @@ public class ActionCore extends PartnerCore<ActionCore> {
     public static final String BUILTIN_LOCATION = "builtin";
     public static final String ORIGIN_LOCATION = "origin";
 
-    private final Lock cacheLock = new ReentrantLock();
     // 由于当前的执行器逻辑实现，平台线程池大小不得小于 2，这里规定为最小为 4
-    private final ExecutorService platformExecutor = Executors
+    private final ExecutorService platformExecutor = Executors.newFixedThreadPool(Math.max(Runtime.getRuntime().availableProcessors(), 4));
-            .newFixedThreadPool(Math.max(Runtime.getRuntime().availableProcessors(), 4));
     private final ExecutorService virtualExecutor = Executors.newVirtualThreadPerTaskExecutor();
+
     /**
      * 已存在的行动程序，键格式为‘<MCP-ServerName>::<Tool-Name>’，值为 MCP Server 通过 Resources 相关渠道传递的行动程序元信息
      */
@@ -50,10 +43,7 @@ public class ActionCore extends PartnerCore<ActionCore> {
      * 持久行动池
      */
     private CopyOnWriteArraySet<ExecutableAction> actionPool = new CopyOnWriteArraySet<>();
-    /**
+
-     * 语义缓存与行为倾向映射
-     */
-    private List<ActionCacheData> actionCache = new ArrayList<>();
     private RunnerClient runnerClient;
 
     public ActionCore() throws IOException, ClassNotFoundException {
@@ -85,59 +75,6 @@ public class ActionCore extends PartnerCore<ActionCore> {
                 .collect(Collectors.toSet());
     }
 
-    /**
-     * 计算输入内容的语义向量，根据与{@link ActionCacheData#getInputVector()}的相似度挑取缓存，后续将根据评估结果来更新计数
-     *
-     * @param input 本次输入内容
-     * @return 命中的行为倾向集合
-     */
-    @CapabilityMethod
-    public List<String> selectTendencyCache(String input) {
-        if (!VectorClient.status) {
-            return null;
-        }
-        VectorClient vectorClient = VectorClient.INSTANCE;
-        // 计算本次输入的向量
-        float[] vector = vectorClient.compute(input);
-        if (vector == null)
-            return null;
-        // 与现有缓存比对，将匹配到的收集并返回
-        return actionCache.parallelStream()
-                .filter(ActionCacheData::isActivated)
-                .filter(data -> {
-                    double compared = vectorClient.compare(vector, data.getInputVector());
-                    return compared > data.getThreshold();
-                })
-                .map(ActionCacheData::getTendency)
-                .collect(Collectors.toList());
-    }
-
-    @CapabilityMethod
-    public void updateTendencyCache(CacheAdjustData data) {
-        VectorClient vectorClient = VectorClient.INSTANCE;
-        List<CacheAdjustMetaData> list = data.getMetaDataList();
-        String input = data.getInput();
-        float[] inputVector = vectorClient.compute(input);
-
-        List<CacheAdjustMetaData> matchAndPassed = new ArrayList<>();
-        List<CacheAdjustMetaData> matchNotPassed = new ArrayList<>();
-        List<CacheAdjustMetaData> notMatchPassed = new ArrayList<>();
-
-        for (CacheAdjustMetaData metaData : list) {
-            if (metaData.isHit() && metaData.isPassed()) {
-                matchAndPassed.add(metaData);
-            } else if (metaData.isHit()) {
-                matchNotPassed.add(metaData);
-            } else if (!metaData.isPassed()) {
-                notMatchPassed.add(metaData);
-            }
-        }
-
-        platformExecutor.execute(() -> adjustMatchAndPassed(matchAndPassed, inputVector, input, vectorClient));
-        platformExecutor.execute(() -> adjustMatchNotPassed(matchNotPassed, vectorClient));
-        platformExecutor.execute(() -> adjustNotMatchPassed(notMatchPassed, inputVector, input, vectorClient));
-    }
-
     @CapabilityMethod
     public ExecutorService getExecutor(ExecutorType type) {
         return switch (type) {
@@ -291,95 +228,6 @@ public class ActionCore extends PartnerCore<ActionCore> {
         executableAction.getHistory().clear();
     }
 
-    /**
-     * 命中缓存且评估通过时
-     *
-     * @param matchAndPassed 该类型的带调整缓存信息列表
-     * @param inputVector    本次输入内容的语义向量
-     * @param vectorClient   向量客户端
-     */
-    private void adjustMatchAndPassed(List<CacheAdjustMetaData> matchAndPassed, float[] inputVector, String input,
-                                      VectorClient vectorClient) {
-        matchAndPassed.forEach(adjustData -> {
-            // 获取原始缓存条目
-            String tendency = adjustData.getTendency();
-            ActionCacheData primaryCacheData = selectCacheData(tendency);
-            if (primaryCacheData == null) {
-                return;
-            }
-            primaryCacheData.updateAfterMatchAndPassed(inputVector, vectorClient, input);
-        });
-    }
-
-    /**
-     * 针对命中缓存、但评估未通过的条目与输入进行处理
-     *
-     * @param matchNotPassed 该类型的带调整缓存信息列表
-     * @param vectorClient   向量客户端
-     */
-    private void adjustMatchNotPassed(List<CacheAdjustMetaData> matchNotPassed, VectorClient vectorClient) {
-        List<ActionCacheData> toRemove = new ArrayList<>();
-        matchNotPassed.forEach(adjustData -> {
-            // 获取原始缓存条目
-            String tendency = adjustData.getTendency();
-            ActionCacheData primaryCacheData = selectCacheData(tendency);
-            if (primaryCacheData == null) {
-                return;
-            }
-            boolean remove = primaryCacheData.updateAfterMatchNotPassed(vectorClient);
-            if (remove) {
-                toRemove.add(primaryCacheData);
-            }
-
-        });
-        cacheLock.lock();
-        actionCache.removeAll(toRemove);
-        cacheLock.unlock();
-    }
-
-    /**
-     * 针对未命中但评估通过的缓存做出调整:
-     * <ol>
-     * <h3>如果存在缓存条目</h3>
-     * <li>
-     * 若已生效，但此时未匹配到则说明尚未生效或者阈值、向量{@link ActionCacheData#getInputVector()}存在问题，调低阈值，同时带权移动平均
-     * </li>
-     * <li>
-     * 若未生效，则只增加计数并带权移动平均
-     * </li>
-     * </ol>
-     * 如果不存在缓存条目，则新增并填充字段
-     *
-     * @param notMatchPassed 该类型的带调整缓存信息列表
-     * @param inputVector    本次输入内容的语义向量
-     * @param input          本次输入内容
-     * @param vectorClient   向量客户端
-     */
-    private void adjustNotMatchPassed(List<CacheAdjustMetaData> notMatchPassed, float[] inputVector, String input,
-                                      VectorClient vectorClient) {
-        notMatchPassed.forEach(adjustData -> {
-            // 获取原始缓存条目
-            String tendency = adjustData.getTendency();
-            ActionCacheData primaryCacheData = selectCacheData(tendency);
-            float[] tendencyVector = vectorClient.compute(tendency);
-            if (primaryCacheData == null) {
-                actionCache.add(new ActionCacheData(tendency, tendencyVector, inputVector, input));
-                return;
-            }
-            primaryCacheData.updateAfterNotMatchPassed(input, inputVector, tendencyVector, vectorClient);
-        });
-    }
-
-    private ActionCacheData selectCacheData(String tendency) {
-        for (ActionCacheData actionCacheData : actionCache) {
-            if (actionCacheData.getTendency().equals(tendency)) {
-                return actionCacheData;
-            }
-        }
-        log.warn("[{}] 未找到行为倾向[{}]对应的缓存条目，可能是代码逻辑存在错误", getCoreKey(), tendency);
-        return null;
-    }
-
     @Override
     protected String getCoreKey() {
         return "action-core";

Partner-Core/src/main/java/work/slhaf/partner/core/action/entity/cache/ActionCacheData.java

@@ -1,181 +0,0 @@
-package work.slhaf.partner.core.action.entity.cache;
-
-import lombok.Data;
-import work.slhaf.partner.common.vector.VectorClient;
-
-import java.util.ArrayList;
-import java.util.List;
-
-@Data
-public class ActionCacheData {
-    private boolean activated = false;
-    private int inputMatchCount = 1;
-
-    private float[] inputVector;
-    private float[] tendencyVector;
-    private String tendency;
-    private double threshold = 0.75;
-
-    private List<String> validSamples = new ArrayList<>();
-    private int failedCount = 0;
-    private Type type = Type.PRIMARY;
-
-    public ActionCacheData(String tendency, float[] tendencyVector, float[] inputVector, String input) {
-        this.tendency = tendency;
-        this.inputVector = inputVector;
-        this.tendencyVector = tendencyVector;
-        this.validSamples.add(input);
-    }
-
-    /**
-     * 命中缓存且评估通过时，根据输入内容的语义向量与现有的输入语义向量进行带权移动平均，以相似度为权重，同时降低失败计数，为零时置为上一级缓存类型{@link ActionCacheData.Type}
-     *
-     * @param inputVector  本次输入内容对应的语义向量
-     * @param vectorClient 向量客户端
-     * @param input        本次输入内容
-     */
-    public synchronized void updateAfterMatchAndPassed(float[] inputVector, VectorClient vectorClient, String input) {
-        updateInputVector(inputVector, vectorClient);
-        addValidSample(input);
-        reduceFailedCount();
-        updateType();
-        addInputMatchCount();
-    }
-
-    private void updateType() {
-        if (this.failedCount == 0) {
-            this.type = switch (type) {
-                case PRIMARY, REBUILD_V1 -> ActionCacheData.Type.PRIMARY;
-                case REBUILD_V2 -> ActionCacheData.Type.REBUILD_V1;
-                case REBUILD_V3 -> ActionCacheData.Type.REBUILD_V2;
-            };
-        }
-    }
-
-    private void reduceFailedCount() {
-        this.failedCount = Math.max(this.failedCount - 1, 0);
-    }
-
-    private void addValidSample(String input) {
-        if (this.validSamples.size() == 12) {
-            this.validSamples.removeFirst();
-        }
-        this.validSamples.add(input);
-    }
-
-    private void updateInputVector(float[] inputVector, VectorClient vectorClient) {
-        this.inputVector = vectorClient.weightedAverage(inputVector, this.inputVector);
-    }
-
-    /**
-     * 针对命中缓存、但评估未通过的条目与输入进行处理: 增加失败计数(必要时重建并更新类型等级)、调高阈值(0.02)，由于缓存匹配但评估未通过，所以不进行带权移动平均
-     *
-     * @param vectorClient 向量客户端
-     * @return 是否需要删除(已在REBUILD_V3状态且达到最大误判次数的)
-     */
-    public synchronized boolean updateAfterMatchNotPassed(VectorClient vectorClient) {
-        adjustThreshold();
-        addFailedCount();
-        if (this.failedCount < 3) {
-            return false;
-        }
-        if (this.type == Type.REBUILD_V3) {
-            return true;
-        }
-        rebuildAndSwitchType(vectorClient);
-        return false;
-    }
-
-    private void rebuildAndSwitchType(VectorClient vectorClient) {
-        this.type = switch (this.type) {
-            case PRIMARY -> {
-                //样本顺序反转后，以全部样本重建
-                this.validSamples = this.validSamples.reversed();
-                rebuildWithSamples(vectorClient);
-                yield Type.REBUILD_V1;
-            }
-            case REBUILD_V1 -> {
-                //截取后一半样本，反转后以此重建
-                List<String> temp = this.validSamples.subList(this.validSamples.size() / 2, this.validSamples.size());
-                this.validSamples = temp.reversed();
-                rebuildWithSamples(vectorClient);
-                yield Type.REBUILD_V2;
-            }
-            case REBUILD_V2 -> {
-                //截取后四分之一样本，反转后以此重建
-                List<String> temp = this.validSamples.subList(this.validSamples.size() / 4, this.validSamples.size());
-                this.validSamples = temp.reversed();
-                rebuildWithSamples(vectorClient);
-                yield Type.REBUILD_V3;
-            }
-            case REBUILD_V3 -> null;
-        };
-        //阈值减0.05，防止重建后一直升高
-        this.threshold = Math.max(this.threshold - 0.05, 0.75);
-        this.failedCount = 0;
-    }
-
-    private void rebuildWithSamples(VectorClient vectorClient) {
-        for (int i = 0; i < this.validSamples.size(); i++) {
-            String sample = this.validSamples.get(i);
-            if (i == 0) {
-                this.inputVector = vectorClient.compute(sample);
-            } else {
-                float[] newSampleVector = vectorClient.compute(sample);
-                this.inputVector = vectorClient.weightedAverage(this.inputVector, newSampleVector);
-            }
-        }
-    }
-
-    private void addFailedCount() {
-        this.failedCount = Math.min(this.failedCount + 1, 3);
-    }
-
-    private void adjustThreshold() {
-        double newThreshold = this.threshold + 0.03;
-        this.threshold = Math.min(newThreshold, 0.95);
-    }
-
-    /**
-     * 针对未命中但评估通过的已存在缓存做出调整:
-     * <ol>
-     *     <li>
-     *         若已生效，但此时未匹配到则说明阈值或者向量{@link ActionCacheData#getInputVector()}存在问题，调低阈值，同时带权移动平均
-     *     </li>
-     *     <li>
-     *         若未生效，则只增加计数并带权移动平均
-     *     </li>
-     * </ol>
-     *
-     * @param input          本次输入内容
-     * @param inputVector    本次输入内容对应的语义向量
-     * @param tendencyVector 本次倾向对应的语义向量
-     * @param vectorClient   向量客户端
-     */
-    public synchronized void updateAfterNotMatchPassed(String input, float[] inputVector, float[] tendencyVector, VectorClient vectorClient) {
-        if (this.activated) {
-            reduceThreshold();
-            this.inputVector = vectorClient.weightedAverage(inputVector, this.inputVector);
-        } else {
-            addValidSample(input);
-            this.tendencyVector = vectorClient.weightedAverage(tendencyVector, this.tendencyVector);
-            addInputMatchCount();
-        }
-    }
-
-    private void reduceThreshold() {
-        double newThreshold = this.threshold - 0.02;
-        this.threshold = Math.max(newThreshold, 0.75);
-    }
-
-    private void addInputMatchCount() {
-        this.inputMatchCount += 1;
-        if (inputMatchCount >= 6) {
-            this.activated = true;
-        }
-    }
-
-    public enum Type {
-        PRIMARY, REBUILD_V1, REBUILD_V2, REBUILD_V3
-    }
-}

Partner-Core/src/main/java/work/slhaf/partner/module/action/planner/ActionPlanner.java

@@ -8,12 +8,9 @@ import work.slhaf.partner.api.agent.factory.capability.annotation.InjectCapabili
 import work.slhaf.partner.api.agent.factory.component.abstracts.AbstractAgentModule;
 import work.slhaf.partner.api.agent.factory.component.annotation.Init;
 import work.slhaf.partner.api.agent.factory.component.annotation.InjectModule;
-import work.slhaf.partner.common.vector.VectorClient;
 import work.slhaf.partner.core.action.ActionCapability;
 import work.slhaf.partner.core.action.ActionCore;
 import work.slhaf.partner.core.action.entity.*;
-import work.slhaf.partner.core.action.entity.cache.CacheAdjustData;
-import work.slhaf.partner.core.action.entity.cache.CacheAdjustMetaData;
 import work.slhaf.partner.core.cognition.BlockContent;
 import work.slhaf.partner.core.cognition.CognitionCapability;
 import work.slhaf.partner.core.cognition.CommunicationBlockContent;
@@ -135,33 +132,11 @@ public class ActionPlanner extends AbstractAgentModule.Running<PartnerRunningFlo
             EvaluatorInput evaluatorInput = assemblyHelper.buildEvaluatorInput(extractorResult);
             List<EvaluatorResult> evaluatorResults = actionEvaluator.execute(evaluatorInput); // 并发操作均为访问
             handleEvaluatorResults(evaluatorResults, source, input);
-            updateTendencyCache(evaluatorResults, input, extractorResult);
 
             cognitionCapability.contextWorkspace().expire(TENDENCIES_EVALUATING_BLOCK_NAME, getModuleName());
         });
     }
 
-    private void updateTendencyCache(List<EvaluatorResult> evaluatorResults, String input, ExtractorResult extractorResult) {
-        if (!VectorClient.status) {
-            return;
-        }
-        executor.execute(() -> {
-            CacheAdjustData data = new CacheAdjustData();
-            List<CacheAdjustMetaData> list = new ArrayList<>();
-            List<String> hitTendencies = extractorResult.getTendencies();
-            for (EvaluatorResult result : evaluatorResults) {
-                CacheAdjustMetaData metaData = new CacheAdjustMetaData();
-                metaData.setTendency(result.getTendency());
-                metaData.setPassed(result.isOk());
-                metaData.setHit(hitTendencies.contains(result.getTendency()));
-                list.add(metaData);
-            }
-            data.setMetaDataList(list);
-            data.setInput(input);
-            actionCapability.updateTendencyCache(data);
-        });
-    }
-
     private void handleEvaluatorResults(List<EvaluatorResult> evaluatorResults, String source, String input) {
         List<ExecutableAction> passedActions = new ArrayList<>();
         int approvedExecutableCount = 0;

Partner-Core/src/main/java/work/slhaf/partner/module/action/planner/extractor/ActionExtractor.java

@@ -5,7 +5,6 @@ import work.slhaf.partner.api.agent.factory.capability.annotation.InjectCapabili
 import work.slhaf.partner.api.agent.factory.component.abstracts.AbstractAgentModule;
 import work.slhaf.partner.api.agent.model.ActivateModel;
 import work.slhaf.partner.api.agent.model.pojo.Message;
-import work.slhaf.partner.core.action.ActionCapability;
 import work.slhaf.partner.core.cognition.CognitionCapability;
 import work.slhaf.partner.core.cognition.ContextBlock;
 import work.slhaf.partner.module.action.planner.extractor.entity.ExtractorResult;
@@ -13,25 +12,18 @@ import work.slhaf.partner.module.action.planner.extractor.entity.ExtractorResult
 import java.util.List;
 
 public class ActionExtractor extends AbstractAgentModule.Sub<String, ExtractorResult> implements ActivateModel {
-    @InjectCapability
+
-    private ActionCapability actionCapability;
     @InjectCapability
     private CognitionCapability cognitionCapability;
 
     @Override
     public ExtractorResult execute(String input) {
-        List<String> tendencyCache = actionCapability.selectTendencyCache(input);
-        if (tendencyCache != null && !tendencyCache.isEmpty()) {
-            ExtractorResult result = new ExtractorResult();
-            result.setTendencies(tendencyCache);
-            return result;
-        }
         for (int i = 0; i < 3; i++) {
             try {
                 List<Message> messages = List.of(
                         cognitionCapability.contextWorkspace().resolve(List.of(
-                                ContextBlock.VisibleDomain.ACTION,
+                                ContextBlock.VisibleDomain.COGNITION,
-                                ContextBlock.VisibleDomain.COGNITION
+                                ContextBlock.VisibleDomain.ACTION
                         )).encodeToMessage(),
                         new Message(Message.Character.USER, input)
                 );