!3 nllp机器翻译支持202种语言互相翻译

Merge pull request !3 from puerile男孩/dev
2026-09-09 19:18:52 +00:00 · 2025-06-14 02:24:42 +00:00
parent 651cd38336 4cb7354410
commit 6f66d8d19e
30 changed files with 2070 additions and 8 deletions
--- a/examples/src/main/java/smartai/examples/nlp/TextTranslationCPU.java
+++ b/examples/src/main/java/smartai/examples/nlp/TextTranslationCPU.java
@@ -0,0 +1,57 @@
+package smartai.examples.nlb;
+
+import ai.djl.Device;
+import ai.djl.ModelException;
+import ai.djl.translate.TranslateException;
+import smartai.examples.nlb.generate.SearchConfig;
+import smartai.examples.nlb.model.NllbModel;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+
+import java.io.IOException;
+
+/**
+ * 文本翻译，支持202种语言互译
+ *
+ * @author Calvin
+ * @mail 179209347@qq.com
+ * @website www.aias.top
+ */
+public final class TextTranslationCPU {
+
+    private static final Logger logger = LoggerFactory.getLogger(TextTranslationCPU.class);
+
+    private TextTranslationCPU() {
+    }
+
+    public static void main(String[] args) throws ModelException, IOException,
+            TranslateException {
+
+        SearchConfig config = new SearchConfig();
+        // 设置输出文字的最大长度
+        config.setMaxSeqLength(128);
+        // 设置源语言：中文 "zho_Hans": 256200
+        config.setSrcLangId(256200);
+        // 设置目标语言：英文 "eng_Latn": 256047
+        config.setForcedBosTokenId(256047);
+        config.setForcedBosTokenId(256201);
+
+        // 输入文字
+        String input = "智利北部的丘基卡马塔矿是世界上最大的露天矿之一，长约4公里，宽3公里，深1公里。";
+
+        String modelPath = "E:\\ai\\models\\nlp\\";
+        String cpuModelName = "traced_translation_cpu.pt";
+        String gpuModelName = "traced_translation_gpu.pt";
+        try (NllbModel nllbModel = new NllbModel(config, modelPath, cpuModelName, Device.cpu())) {
+
+            System.setProperty("ai.djl.pytorch.graph_optimizer", "false");
+
+            // 运行模型，获取翻译结果
+            String result = nllbModel.translate(input);
+
+            logger.info("result========={}", result);
+        } finally {
+            System.clearProperty("ai.djl.pytorch.graph_optimizer");
+        }
+    }
+}
--- a/examples/src/main/java/smartai/examples/nlp/generate/BatchTensorList.java
+++ b/examples/src/main/java/smartai/examples/nlp/generate/BatchTensorList.java
@@ -0,0 +1,174 @@
+/*
+ * Copyright 2023 Amazon.com, Inc. or its affiliates. All Rights Reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License"). You may not use this file except in compliance
+ * with the License. A copy of the License is located at
+ *
+ * http://aws.amazon.com/apache2.0/
+ *
+ * or in the "license" file accompanying this file. This file is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES
+ * OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions
+ * and limitations under the License.
+ */
+package smartai.examples.nlb.generate;
+
+import ai.djl.ndarray.NDArray;
+import ai.djl.ndarray.NDList;
+
+/**
+ * BatchTensorList represents a search state, and the NDArrays inside are updated in each iteration
+ * of the autoregressive loop.
+ *
+ * <p>It is a struct consisting of NDArrays, whose first dimension is batch, and also contains
+ * sequence dimension (whose position in tensor's shape is specified by seqDimOrder). The SeqBatcher
+ * batch operations will operate on these two dimensions.
+ */
+public abstract class BatchTensorList {
+    // [batch, seq_past]. seq-dim-size == |past_seq| + |inputIds|. Will grow.
+    private NDArray pastOutputIds;
+
+    // [batch, seq_past]
+    // The cache of past attentionMask. seq-dim-size == |past_seq| + |inputIds|. Will grow.
+    private NDArray pastAttentionMask;
+
+    // (k, v) * numLayer,
+    // kv: [batch, heads, seq_past, kvfeature]
+    // The cache of past sequence. seq-dim-size == |past_seq| + |inputIds|. Will grow.
+    private NDList pastKeyValues;
+
+    // Sequence dimension order among all dimensions for each element in the batch list.
+    private long[] seqDimOrder;
+
+    BatchTensorList() {}
+
+    /**
+     * Constructs a new {@code BatchTensorList} instance.
+     *
+     * @param list the NDList that contains the serialized version of the batch tensors
+     * @param seqDimOrder the sequence dimension order that specifies where the sequence dimension
+     *     is in a tensor's shape
+     */
+    BatchTensorList(NDList list, long[] seqDimOrder) {
+        this.seqDimOrder = seqDimOrder;
+        pastOutputIds = list.get(0);
+        pastAttentionMask = list.get(1);
+        pastKeyValues = list.subNDList(2);
+    }
+
+    /**
+     * Constructs a new {@code BatchTensorList} instance.
+     *
+     * @param pastOutputIds past output token ids
+     * @param pastAttentionMask past attention mask
+     * @param pastKeyValues past kv cache
+     * @param seqDimOrder the sequence dimension order that specifies where the sequence dimension
+     *     is in a tensor's shape
+     */
+    BatchTensorList(
+            NDArray pastOutputIds,
+            NDArray pastAttentionMask,
+            NDList pastKeyValues,
+            long[] seqDimOrder) {
+        this.pastKeyValues = pastKeyValues;
+        this.pastOutputIds = pastOutputIds;
+        this.pastAttentionMask = pastAttentionMask;
+        this.seqDimOrder = seqDimOrder;
+    }
+
+    /**
+     * Constructs a new {@code BatchTensorList} instance from the serialized version of the batch
+     * tensors.
+     *
+     * <p>The pastOutputIds has to be the first in the output list.
+     *
+     * @param inputList the serialized version of the batch tensors
+     * @param seqDimOrder the sequence dimension order that specifies where the sequence dimension
+     *     is in a tensor's shape
+     * @return BatchTensorList
+     */
+    public abstract BatchTensorList fromList(NDList inputList, long[] seqDimOrder);
+
+    /**
+     * Returns the serialized version of the BatchTensorList. The pastOutputIds has to be the first
+     * in the output list.
+     *
+     * @return the NDList that contains the serialized BatchTensorList
+     */
+    public abstract NDList getList();
+
+    /**
+     * Returns the sequence dimension order which specifies where the sequence dimension is in a
+     * tensor's shape.
+     *
+     * @return the sequence dimension order which specifies where the sequence dimension is in a
+     *     tensor's shape
+     */
+    public long[] getSeqDimOrder() {
+        return seqDimOrder;
+    }
+
+    /**
+     * Returns the value of the pastOutputIds.
+     *
+     * @return the value of pastOutputIds
+     */
+    public NDArray getPastOutputIds() {
+        return pastOutputIds;
+    }
+
+    /**
+     * Sets the past output token ids.
+     *
+     * @param pastOutputIds the past output token ids
+     */
+    public void setPastOutputIds(NDArray pastOutputIds) {
+        this.pastOutputIds = pastOutputIds;
+    }
+
+    /**
+     * Returns the value of the pastAttentionMask.
+     *
+     * @return the value of pastAttentionMask
+     */
+    public NDArray getPastAttentionMask() {
+        return pastAttentionMask;
+    }
+
+    /**
+     * Sets the attention mask.
+     *
+     * @param pastAttentionMask the attention mask
+     */
+    public void setPastAttentionMask(NDArray pastAttentionMask) {
+        this.pastAttentionMask = pastAttentionMask;
+    }
+
+    /**
+     * Returns the value of the pastKeyValues.
+     *
+     * @return the value of pastKeyValues
+     */
+    public NDList getPastKeyValues() {
+        return pastKeyValues;
+    }
+
+    /**
+     * Sets the kv cache.
+     *
+     * @param pastKeyValues the kv cache
+     */
+    public void setPastKeyValues(NDList pastKeyValues) {
+        this.pastKeyValues = pastKeyValues;
+    }
+
+    /**
+     * Sets the sequence dimension order which specifies where the sequence dimension is in a
+     * tensor's shape.
+     *
+     * @param seqDimOrder the sequence dimension order which specifies where the sequence dimension
+     *     is in a tensor's shape
+     */
+    public void setSeqDimOrder(long[] seqDimOrder) {
+        this.seqDimOrder = seqDimOrder;
+    }
+}
--- a/examples/src/main/java/smartai/examples/nlp/generate/CausalLMOutput.java
+++ b/examples/src/main/java/smartai/examples/nlp/generate/CausalLMOutput.java
@@ -0,0 +1,32 @@
+package smartai.examples.nlb.generate;
+
+import ai.djl.ndarray.NDArray;
+import ai.djl.ndarray.NDList;
+/**
+ * 解码输出对象
+ *
+ * @author Calvin
+ * @mail 179209347@qq.com
+ * @website www.aias.top
+ */
+public class CausalLMOutput {
+    private NDArray logits;
+    private NDList pastKeyValuesList;
+
+    public CausalLMOutput(NDArray logits, NDList pastKeyValues) {
+        this.logits = logits;
+        this.pastKeyValuesList = pastKeyValues;
+    }
+
+    public NDArray getLogits() {
+        return logits;
+    }
+
+    public void setLogits(NDArray logits) {
+        this.logits = logits;
+    }
+
+    public NDList getPastKeyValuesList() {
+        return pastKeyValuesList;
+    }
+}
--- a/examples/src/main/java/smartai/examples/nlp/generate/GreedyBatchTensorList.java
+++ b/examples/src/main/java/smartai/examples/nlp/generate/GreedyBatchTensorList.java
@@ -0,0 +1,84 @@
+package smartai.examples.nlb.generate;
+
+import ai.djl.ndarray.NDArray;
+import ai.djl.ndarray.NDList;
+
+/**
+ * 贪婪搜索张量对象列表
+ *
+ * @author Calvin
+ * @mail 179209347@qq.com
+ * @website www.aias.top
+ */
+public class GreedyBatchTensorList extends BatchTensorList {
+    // [batch, 1]
+    private NDArray nextInputIds;
+
+    private NDArray pastOutputIds;
+
+    private NDArray encoderHiddenStates;
+    private NDArray attentionMask;
+    private NDList pastKeyValues;
+
+    public GreedyBatchTensorList(
+            NDArray nextInputIds,
+            NDArray pastOutputIds,
+            NDList pastKeyValues,
+            NDArray encoderHiddenStates,
+            NDArray attentionMask) {
+        this.nextInputIds = nextInputIds;
+        this.pastKeyValues = pastKeyValues;
+        this.pastOutputIds = pastOutputIds;
+        this.attentionMask = attentionMask;
+        this.encoderHiddenStates = encoderHiddenStates;
+    }
+
+    public GreedyBatchTensorList() {}
+
+    public BatchTensorList fromList(NDList inputList, long[] seqDimOrder) {
+        return new GreedyBatchTensorList();
+    }
+
+    public NDList getList() {
+        return new NDList();
+    }
+
+    public NDArray getNextInputIds() {
+        return nextInputIds;
+    }
+
+    public void setNextInputIds(NDArray nextInputIds) {
+        this.nextInputIds = nextInputIds;
+    }
+    public NDArray getPastOutputIds() {
+        return pastOutputIds;
+    }
+
+    public void setPastOutputIds(NDArray pastOutputIds) {
+        this.pastOutputIds = pastOutputIds;
+    }
+
+    public NDList getPastKeyValues() {
+        return pastKeyValues;
+    }
+
+    public void setPastKeyValues(NDList pastKeyValues) {
+        this.pastKeyValues = pastKeyValues;
+    }
+
+    public NDArray getEncoderHiddenStates() {
+        return encoderHiddenStates;
+    }
+
+    public void setEncoderHiddenStates(NDArray encoderHiddenStates) {
+        this.encoderHiddenStates = encoderHiddenStates;
+    }
+
+    public NDArray getAttentionMask() {
+        return attentionMask;
+    }
+
+    public void setAttentionMask(NDArray attentionMask) {
+        this.attentionMask = attentionMask;
+    }
+}
--- a/examples/src/main/java/smartai/examples/nlp/generate/SearchConfig.java
+++ b/examples/src/main/java/smartai/examples/nlp/generate/SearchConfig.java
@@ -0,0 +1,104 @@
+package smartai.examples.nlb.generate;
+/**
+ * 配置信息
+ *
+ * @author Calvin
+ * @mail 179209347@qq.com
+ * @website www.aias.top
+ */
+public class SearchConfig {
+
+    private int maxSeqLength;
+    private long padTokenId;
+    private long eosTokenId;
+    private long bosTokenId;
+    private long decoderStartTokenId;
+    private float encoderRepetitionPenalty;
+    private long forcedBosTokenId;
+    private long srcLangId;
+    private float lengthPenalty;
+    public SearchConfig() {
+        this.maxSeqLength = 512;
+        this.eosTokenId = 2;
+        this.bosTokenId = 0;
+        this.padTokenId = 1;
+        this.decoderStartTokenId = 2;
+        this.encoderRepetitionPenalty = 1.0f;
+        this.srcLangId = 0;
+        this.forcedBosTokenId = 0;
+        this.lengthPenalty = 1.0f;
+
+    }
+
+    public long getSrcLangId() {
+        return srcLangId;
+    }
+
+    public void setSrcLangId(long srcLangId) {
+        this.srcLangId = srcLangId;
+    }
+
+    public void setEosTokenId(long eosTokenId) {
+        this.eosTokenId = eosTokenId;
+    }
+
+    public int getMaxSeqLength() {
+        return maxSeqLength;
+    }
+
+    public void setMaxSeqLength(int maxSeqLength) {
+        this.maxSeqLength = maxSeqLength;
+    }
+
+    public long getPadTokenId() {
+        return padTokenId;
+    }
+
+    public void setPadTokenId(long padTokenId) {
+        this.padTokenId = padTokenId;
+    }
+
+    public long getEosTokenId() {
+        return eosTokenId;
+    }
+
+    public long getDecoderStartTokenId() {
+        return decoderStartTokenId;
+    }
+
+    public void setDecoderStartTokenId(long decoderStartTokenId) {
+        this.decoderStartTokenId = decoderStartTokenId;
+    }
+
+    public float getEncoderRepetitionPenalty() {
+        return encoderRepetitionPenalty;
+    }
+
+    public void setEncoderRepetitionPenalty(float encoderRepetitionPenalty) {
+        this.encoderRepetitionPenalty = encoderRepetitionPenalty;
+    }
+
+    public long getForcedBosTokenId() {
+        return forcedBosTokenId;
+    }
+
+    public void setForcedBosTokenId(long forcedBosTokenId) {
+        this.forcedBosTokenId = forcedBosTokenId;
+    }
+
+    public float getLengthPenalty() {
+        return lengthPenalty;
+    }
+
+    public void setLengthPenalty(float lengthPenalty) {
+        this.lengthPenalty = lengthPenalty;
+    }
+
+    public long getBosTokenId() {
+        return bosTokenId;
+    }
+
+    public void setBosTokenId(long bosTokenId) {
+        this.bosTokenId = bosTokenId;
+    }
+}
--- a/examples/src/main/java/smartai/examples/nlp/model/Decoder2Translator.java
+++ b/examples/src/main/java/smartai/examples/nlp/model/Decoder2Translator.java
@@ -0,0 +1,45 @@
+package smartai.examples.nlb.model;
+
+import ai.djl.ndarray.NDArray;
+import ai.djl.ndarray.NDList;
+import ai.djl.translate.NoBatchifyTranslator;
+import ai.djl.translate.TranslatorContext;
+import smartai.examples.nlb.generate.CausalLMOutput;
+
+/**
+ * 解碼器，參數支持 pastKeyValues
+ *
+ * @author Calvin
+ * @mail 179209347@qq.com
+ * @website www.aias.top
+ */
+public class Decoder2Translator implements NoBatchifyTranslator<NDList, CausalLMOutput> {
+    private String tupleName;
+
+    public Decoder2Translator() {
+        tupleName = "past_key_values(" + 12 + ',' + 4 + ')';
+    }
+
+    @Override
+    public NDList processInput(TranslatorContext ctx, NDList input) {
+
+        NDArray placeholder = ctx.getNDManager().create(0);
+        placeholder.setName("module_method:decoder2");
+
+        input.add(placeholder);
+
+        return input;
+    }
+
+    @Override
+    public CausalLMOutput processOutput(TranslatorContext ctx, NDList output) {
+        NDArray logitsOutput = output.get(0);
+        NDList pastKeyValuesOutput = output.subNDList(1, 12 * 4 + 1);
+
+        for (NDArray array : pastKeyValuesOutput) {
+            array.setName(tupleName);
+        }
+
+        return new CausalLMOutput(logitsOutput, pastKeyValuesOutput);
+    }
+}
--- a/examples/src/main/java/smartai/examples/nlp/model/DecoderTranslator.java
+++ b/examples/src/main/java/smartai/examples/nlp/model/DecoderTranslator.java
@@ -0,0 +1,44 @@
+package smartai.examples.nlb.model;
+
+import ai.djl.ndarray.NDArray;
+import ai.djl.ndarray.NDList;
+import ai.djl.translate.NoBatchifyTranslator;
+import ai.djl.translate.TranslatorContext;
+import smartai.examples.nlb.generate.CausalLMOutput;
+/**
+ * 解碼器，參數沒有 pastKeyValues
+ *
+ * @author Calvin
+ * @mail 179209347@qq.com
+ * @website www.aias.top
+ */
+public class DecoderTranslator implements NoBatchifyTranslator<NDList, CausalLMOutput> {
+    private String tupleName;
+
+    public DecoderTranslator() {
+        tupleName = "past_key_values(" + 12 + ',' + 4 + ')';
+    }
+
+    @Override
+    public NDList processInput(TranslatorContext ctx, NDList input) {
+
+        NDArray placeholder = ctx.getNDManager().create(0);
+        placeholder.setName("module_method:decoder");
+
+        input.add(placeholder);
+
+        return input;
+    }
+
+    @Override
+    public CausalLMOutput processOutput(TranslatorContext ctx, NDList output) {
+        NDArray logitsOutput = output.get(0);
+        NDList pastKeyValuesOutput = output.subNDList(1, 12 * 4 + 1);
+
+        for (NDArray array : pastKeyValuesOutput) {
+            array.setName(tupleName);
+        }
+
+        return new CausalLMOutput(logitsOutput, pastKeyValuesOutput);
+    }
+}
--- a/examples/src/main/java/smartai/examples/nlp/model/EncoderTranslator.java
+++ b/examples/src/main/java/smartai/examples/nlp/model/EncoderTranslator.java
@@ -0,0 +1,49 @@
+package smartai.examples.nlb.model;
+
+import ai.djl.ndarray.NDArray;
+import ai.djl.ndarray.NDList;
+import ai.djl.ndarray.NDManager;
+import ai.djl.translate.NoBatchifyTranslator;
+import ai.djl.translate.TranslatorContext;
+
+import java.util.Arrays;
+
+/**
+ * 编码器前后处理
+ *
+ * @author Calvin
+ * @mail 179209347@qq.com
+ * @website www.aias.top
+ */
+public class EncoderTranslator implements NoBatchifyTranslator<long[], NDArray> {
+
+
+    public EncoderTranslator() {
+    }
+
+    @Override
+    public NDList processInput(TranslatorContext ctx, long[] input) throws Exception {
+        NDManager manager = ctx.getNDManager();
+
+        NDArray inputIdArray = manager.create(input).expandDims(0);
+        inputIdArray.setName("input_ids");
+
+        long[] attentionMask = new long[input.length];
+        Arrays.fill(attentionMask, 1);
+        NDArray attentionMaskArray = manager.create(attentionMask).expandDims(0);
+        attentionMaskArray.setName("attention_mask");
+
+        NDArray placeholder = ctx.getNDManager().create(0);
+        placeholder.setName("module_method:encoder");
+
+        return new NDList(inputIdArray, attentionMaskArray, placeholder);
+    }
+
+    @Override
+    public NDArray processOutput(TranslatorContext ctx, NDList list) {
+        NDArray encoderHiddenStates = list.get(0);
+        encoderHiddenStates.detach();
+        return encoderHiddenStates;
+    }
+
+}
--- a/examples/src/main/java/smartai/examples/nlp/model/NllbModel.java
+++ b/examples/src/main/java/smartai/examples/nlp/model/NllbModel.java
@@ -0,0 +1,183 @@
+package smartai.examples.nlb.model;
+
+import ai.djl.Device;
+import ai.djl.ModelException;
+import ai.djl.huggingface.tokenizers.Encoding;
+import ai.djl.huggingface.tokenizers.HuggingFaceTokenizer;
+import ai.djl.inference.Predictor;
+import ai.djl.ndarray.NDArray;
+import ai.djl.ndarray.NDList;
+import ai.djl.ndarray.NDManager;
+import ai.djl.ndarray.index.NDIndex;
+import ai.djl.repository.zoo.Criteria;
+import ai.djl.repository.zoo.ZooModel;
+import ai.djl.translate.NoopTranslator;
+import ai.djl.translate.TranslateException;
+import smartai.examples.nlb.generate.CausalLMOutput;
+import smartai.examples.nlb.generate.GreedyBatchTensorList;
+import smartai.examples.nlb.generate.SearchConfig;
+import smartai.examples.nlb.tokenizer.TokenUtils;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+
+import java.io.IOException;
+import java.nio.file.Paths;
+import java.util.Arrays;
+/**
+ * 模型载入及推理
+ *
+ * @author Calvin
+ * @mail 179209347@qq.com
+ * @website www.aias.top
+ */
+public class NllbModel implements AutoCloseable {
+    private static final Logger logger = LoggerFactory.getLogger(NllbModel.class);
+    private SearchConfig config;
+    private ZooModel<NDList, NDList> nllbModel;
+    private HuggingFaceTokenizer tokenizer;
+    private Predictor<long[], NDArray> encoderPredictor;
+    private Predictor<NDList, CausalLMOutput> decoderPredictor;
+    private Predictor<NDList, CausalLMOutput> decoder2Predictor;
+    private NDManager manager;
+
+    public NllbModel(SearchConfig config, String modelPath, String modelName, Device device) throws ModelException, IOException {
+        this.config = config;
+        Criteria<NDList, NDList> criteria =
+                Criteria.builder()
+                        .setTypes(NDList.class, NDList.class)
+                        .optModelPath(Paths.get(modelPath + modelName))
+                        .optEngine("PyTorch")
+                        .optDevice(device)
+                        .optTranslator(new NoopTranslator())
+                        .build();
+
+        manager = NDManager.newBaseManager(device);
+        nllbModel = criteria.loadModel();
+        tokenizer = HuggingFaceTokenizer.newInstance(Paths.get(modelPath + "tokenizer.json"));
+        encoderPredictor = nllbModel.newPredictor(new EncoderTranslator());
+        decoderPredictor = nllbModel.newPredictor(new DecoderTranslator());
+        decoder2Predictor = nllbModel.newPredictor(new Decoder2Translator());
+    }
+
+    public NDArray encoder(long[] ids) throws TranslateException {
+        return encoderPredictor.predict(ids);
+    }
+
+    public CausalLMOutput decoder(NDList input) throws TranslateException {
+        return decoderPredictor.predict(input);
+    }
+
+    public CausalLMOutput decoder2(NDList input) throws TranslateException {
+        return decoder2Predictor.predict(input);
+    }
+
+    @Override
+    public void close() {
+        encoderPredictor.close();
+        decoderPredictor.close();
+        decoder2Predictor.close();
+        nllbModel.close();
+        manager.close();
+        tokenizer.close();
+    }
+
+    public String translate(String input) throws TranslateException {
+
+        Encoding encoding = tokenizer.encode(input);
+        long[] ids = encoding.getIds();
+        // 1. Encoder
+        long[] inputIds = new long[ids.length];
+        // 设置源语言编码
+        inputIds[0] = config.getSrcLangId();
+        for (int i = 0; i < ids.length - 1; i++) {
+            inputIds[i + 1] = ids[i];
+        }
+        logger.info("inputIds: " + Arrays.toString(inputIds));
+        long[] attentionMask = encoding.getAttentionMask();
+        NDArray attentionMaskArray = manager.create(attentionMask).expandDims(0);
+
+        NDArray encoderHiddenStates = encoder(inputIds);
+
+        NDArray decoder_input_ids = manager.create(new long[]{config.getDecoderStartTokenId()}).reshape(1, 1);
+        NDList decoderInput = new NDList(decoder_input_ids, encoderHiddenStates, attentionMaskArray);
+
+        // 2. Initial Decoder
+        CausalLMOutput modelOutput = decoder(decoderInput);
+        modelOutput.getLogits().attach(manager);
+        modelOutput.getPastKeyValuesList().attach(manager);
+
+        GreedyBatchTensorList searchState =
+                new GreedyBatchTensorList(null, decoder_input_ids, modelOutput.getPastKeyValuesList(), encoderHiddenStates, attentionMaskArray);
+
+        while (true) {
+//            try (NDScope ignore = new NDScope()) {
+            NDArray pastOutputIds = searchState.getPastOutputIds();
+
+            if (searchState.getNextInputIds() != null) {
+                decoderInput = new NDList(searchState.getNextInputIds(), searchState.getEncoderHiddenStates(), searchState.getAttentionMask());
+                decoderInput.addAll(searchState.getPastKeyValues());
+                // 3. Decoder loop
+                modelOutput = decoder2(decoderInput);
+            }
+
+            NDArray outputIds = greedyStepGen(config, pastOutputIds, modelOutput.getLogits());
+
+            searchState.setNextInputIds(outputIds);
+            pastOutputIds = pastOutputIds.concat(outputIds, 1);
+            searchState.setPastOutputIds(pastOutputIds);
+
+            searchState.setPastKeyValues(modelOutput.getPastKeyValuesList());
+
+            // memory management
+//                NDScope.unregister(outputIds, pastOutputIds);
+//        }
+
+            // Termination Criteria
+            long id = searchState.getNextInputIds().toLongArray()[0];
+            if (config.getEosTokenId() == id) {
+                searchState.setNextInputIds(null);
+                break;
+            }
+            if (searchState.getPastOutputIds() != null && searchState.getPastOutputIds().getShape().get(1) + 1 >= config.getMaxSeqLength()) {
+                break;
+            }
+        }
+
+        if (searchState.getNextInputIds() == null) {
+            NDArray resultIds = searchState.getPastOutputIds();
+            String result = TokenUtils.decode(config, tokenizer, resultIds);
+            return result;
+        } else {
+            NDArray resultIds = searchState.getPastOutputIds(); // .concat(searchState.getNextInputIds(), 1)
+            String result = TokenUtils.decode(config, tokenizer, resultIds);
+            return result;
+        }
+
+    }
+
+    public NDArray greedyStepGen(SearchConfig config, NDArray pastOutputIds, NDArray next_token_scores) {
+        next_token_scores = next_token_scores.get(":, -1, :");
+
+        NDArray new_next_token_scores = manager.create(next_token_scores.getShape(), next_token_scores.getDataType());
+        next_token_scores.copyTo(new_next_token_scores);
+
+        // LogitsProcessor 1. ForcedBOSTokenLogitsProcessor
+        // 设置目标语言
+        long cur_len = pastOutputIds.getShape().getLastDimension();
+        if (cur_len == 1) {
+            long num_tokens = new_next_token_scores.getShape().getLastDimension();
+            for (long i = 0; i < num_tokens; i++) {
+                if (i != config.getForcedBosTokenId()) {
+                    new_next_token_scores.set(new NDIndex(":," + i), Float.NEGATIVE_INFINITY);
+                }
+            }
+            new_next_token_scores.set(new NDIndex(":," + config.getForcedBosTokenId()), 0);
+        }
+
+        NDArray probs = new_next_token_scores.softmax(-1);
+        NDArray next_tokens = probs.argMax(-1);
+
+        return next_tokens.expandDims(0);
+    }
+
+}
--- a/examples/src/main/java/smartai/examples/objectdetection/ObjectDetection.java
+++ b/examples/src/main/java/smartai/examples/objectdetection/ObjectDetection.java
@@ -111,18 +111,21 @@ public class ObjectDetection {


    /**
-     * 使用yolo官方模型检测
+     * 使用yolo官方模型检测物品识别
     */
    @Test
    public void objectDetectionWithOfficialModel(){
        DetectorModelConfig config = new DetectorModelConfig();
+        config.setThreshold(0.3f);
        //也支持YoloV8：YOLOV8_OFFICIAL 模型可以从文档中提供的地址下载
        config.setModelEnum(DetectorModelEnum.YOLOV12_OFFICIAL);//检测模型，目前支持19种模型
        // 指定模型路径，需要更改为自己的模型路径
-        config.setModelPath("/Users/xxx/Documents/develop/face_model/yolov12n.onnx");
+        config.setModelPath("E:\\ai\\models\\yolo12m\\yolov12m.onnx");
        DetectorModel detectorModel = ObjectDetectionModelFactory.getInstance().getModel(config);
        //一定要将yolo官方的类别文件：synset.txt（文档中下载）放在模型同目录下，否则报错
-        detectorModel.detectAndDraw("src/main/resources/object_detection.jpg","output/object_detection_detected.png");
+        DetectionResponse detect = detectorModel.detect("E:\\ai\\testimage\\1.jpg");
+        log.info("目标检测结果：{}", JSONObject.toJSONString(detect));
+        detectorModel.detectAndDraw("E:\\ai\\testimage\\1.jpg","E:\\ai\\outimage\\11.png");
    }

    /**
--- a/pom.xml
+++ b/pom.xml
@@ -12,6 +12,7 @@
    <description>SmartJavaAI</description>
    <modules>
        <module>smartjavaai-face</module>
+        <module>smartjavaai-translate</module>
        <module>smartjavaai-common</module>
        <module>smartjavaai-objectdetection</module>
        <module>smartjavaai-all</module>
@@ -53,14 +54,16 @@
            <groupId>ai.djl</groupId>
            <artifactId>model-zoo</artifactId>
        </dependency>
+        <dependency>
+            <groupId>ai.djl.huggingface</groupId>
+            <artifactId>tokenizers</artifactId>
+            <version>${djl.version}</version>
+        </dependency>
 <!--        <dependency>-->
 <!--            <groupId>ai.djl.timeseries</groupId>-->
 <!--            <artifactId>timeseries</artifactId>-->
 <!--        </dependency>-->
-<!--        <dependency>-->
-<!--            <groupId>ai.djl.huggingface</groupId>-->
-<!--            <artifactId>tokenizers</artifactId>-->
-<!--        </dependency>-->
+
 <!--        <dependency>-->
 <!--            <groupId>ai.djl.audio</groupId>-->
 <!--            <artifactId>audio</artifactId>-->
--- a/smartjavaai-common/src/main/java/cn/smartjavaai/common/pool/ZooModelFactory.java
+++ b/smartjavaai-common/src/main/java/cn/smartjavaai/common/pool/ZooModelFactory.java
@@ -0,0 +1,35 @@
+package cn.smartjavaai.common.pool;
+
+import ai.djl.inference.Predictor;
+import ai.djl.repository.zoo.ZooModel;
+import org.apache.commons.pool2.BasePooledObjectFactory;
+import org.apache.commons.pool2.PooledObject;
+import org.apache.commons.pool2.impl.DefaultPooledObject;
+
+/**
+ * ZooModel 工厂类
+ * @author lwx
+ * @date 2025/6/06
+ */
+public class ZooModelFactory<I, O> extends BasePooledObjectFactory<ZooModel<I, O>> {
+    private final ZooModel<I, O> model;
+
+    public ZooModelFactory(ZooModel<I, O> model) {
+        this.model = model;
+    }
+
+    @Override
+    public ZooModel<I, O> create() {
+        return model;
+    }
+
+    @Override
+    public PooledObject<ZooModel<I, O>> wrap(ZooModel<I, O> predictor) {
+        return new DefaultPooledObject<>(predictor);
+    }
+
+    @Override
+    public void destroyObject(PooledObject<ZooModel<I, O>> p) {
+        p.getObject().close();
+    }
+}
--- a/smartjavaai-objectdetection/src/main/java/cn/smartjavaai/objectdetection/enums/DetectorModelEnum.java
+++ b/smartjavaai-objectdetection/src/main/java/cn/smartjavaai/objectdetection/enums/DetectorModelEnum.java
@@ -9,7 +9,7 @@ public enum DetectorModelEnum {

    // resnet50 系列
    SSD_300_RESNET50("ai.djl.pytorch/ssd/0.0.1/ssd_300_resnet50"),
-    SSD_512_RESNET50_V1_VOC("ai.djl.mxnet/ssd/0.0.1/ssd_512_resnet50_v1_voc"),
+    SSD_512_RESNET50_V1_VOC("ai.djl./ssd/0.0.1/ssd_512_resnet50_v1_voc"),

    // vgg16 系列
    SSD_512_VGG16_ATROUS_COCO("ai.djl.mxnet/ssd/0.0.1/ssd_512_vgg16_atrous_coco"),
--- a/smartjavaai-translate/pom.xml
+++ b/smartjavaai-translate/pom.xml
@@ -0,0 +1,134 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project xmlns="http://maven.apache.org/POM/4.0.0"
+         xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
+         xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
+    <modelVersion>4.0.0</modelVersion>
+    <parent>
+        <groupId>cn.smartjavaai</groupId>
+        <artifactId>smartjavaai-parent</artifactId>
+        <version>1.0.15</version>
+    </parent>
+
+    <artifactId>smartjavaai-translate</artifactId>
+
+
+    <dependencies>
+        <dependency>
+            <groupId>cn.smartjavaai</groupId>
+            <artifactId>smartjavaai-common</artifactId>
+            <version>${project.version}</version>
+        </dependency>
+        <dependency>
+            <groupId>junit</groupId>
+            <artifactId>junit</artifactId>
+            <version>4.13.1</version>
+            <scope>compile</scope>
+        </dependency>
+    </dependencies>
+
+    <version>1.0.15</version>
+    <name>smartjavaai-ocr</name>
+    <description>SmartJavaAI</description>
+    <url>https://github.com/geekwenjie/SmartJavaAI</url>
+    <licenses>
+        <license>
+            <name>MIT License</name>
+            <url>https://opensource.org/licenses/MIT</url>
+        </license>
+    </licenses>
+
+    <build>
+        <plugins>
+            <plugin>
+                <groupId>org.sonatype.central</groupId>
+                <artifactId>central-publishing-maven-plugin</artifactId>
+                <version>0.4.0</version>
+                <extensions>true</extensions>
+                <configuration>
+                    <publishingServerId>dengwenjie</publishingServerId>
+                    <tokenAuth>true</tokenAuth>
+                    <deploymentName>${project.groupId}:${project.artifactId}:${project.version}</deploymentName>
+                </configuration>
+            </plugin>
+
+            <plugin>
+                <groupId>org.apache.maven.plugins</groupId>
+                <artifactId>maven-source-plugin</artifactId>
+                <version>3.1.0</version>
+                <executions>
+                    <execution>
+                        <id>attach-sources</id>
+                        <goals>
+                            <goal>jar-no-fork</goal>
+                        </goals>
+                    </execution>
+                </executions>
+            </plugin>
+            <plugin>
+                <groupId>org.apache.maven.plugins</groupId>
+                <artifactId>maven-javadoc-plugin</artifactId>
+                <version>3.1.0</version>
+                <configuration>
+<!--                    <javadocExecutable>${java.home}/bin/javadoc</javadocExecutable>-->
+                    <doclint>none</doclint>
+                    <additionalJOptions>
+                        <additionalJOption>-Xdoclint:none</additionalJOption>
+                    </additionalJOptions>
+                </configuration>
+                <executions>
+                    <execution>
+                        <id>attach-javadocs</id>
+                        <goals>
+                            <goal>jar</goal>
+                        </goals>
+                    </execution>
+                </executions>
+            </plugin>
+            <plugin>
+                <groupId>org.apache.maven.plugins</groupId>
+                <artifactId>maven-gpg-plugin</artifactId>
+                <version>3.1.0</version>
+                <executions>
+                    <execution>
+                        <id>sign-artifacts</id>
+                        <phase>verify</phase>
+                        <goals>
+                            <goal>sign</goal>
+                        </goals>
+                    </execution>
+                </executions>
+            </plugin>
+        </plugins>
+    </build>
+
+    <!-- 必须添加：SCM信息 -->
+    <scm>
+        <connection>scm:git:git://github.com/geekwenjie/SmartJavaAI.git</connection>
+        <developerConnection>scm:git:ssh://github.com/geekwenjie/SmartJavaAI.git</developerConnection>
+        <url>http://github.com/geekwenjie/SmartJavaAI/tree/master</url>
+    </scm>
+
+
+    <distributionManagement>
+        <snapshotRepository>
+            <id>dengwenjie</id>
+            <url>https://s01.oss.sonatype.org/content/repositories/snapshots</url>
+        </snapshotRepository>
+        <repository>
+            <id>dengwenjie</id>
+            <url>https://s01.oss.sonatype.org/service/local/staging/deploy/maven2/</url>
+        </repository>
+    </distributionManagement>
+
+    <developers>
+        <developer>
+            <name>dengwenjie</name>
+            <email>775747758@qq.com</email>
+            <roles>
+                <role>Project Manager</role>
+                <role>Architect</role>
+            </roles>
+        </developer>
+    </developers>
+
+</project>
--- a/smartjavaai-translate/src/main/java/cn/smartjavaai/translation/config/MachineTranslationModelConfig.java
+++ b/smartjavaai-translate/src/main/java/cn/smartjavaai/translation/config/MachineTranslationModelConfig.java
@@ -0,0 +1,40 @@
+package cn.smartjavaai.translation.config;
+
+import cn.smartjavaai.common.enums.DeviceEnum;
+
+import cn.smartjavaai.translation.enums.MachineTranslationModeEnum;
+import lombok.Data;
+
+/**
+ * 机器翻译模型配置
+ * @author lwx
+ * @date 2025/6/05
+ */
+@Data
+public class MachineTranslationModelConfig {
+    /**
+     * 翻译模型
+     */
+    private MachineTranslationModeEnum modelEnum;
+
+    /**
+     * 设备类型
+     */
+    private DeviceEnum device;
+
+    /**
+     * 翻译模型路径
+     */
+    private String modelPath;
+    /**
+     * 翻译模型路径
+     */
+    private String modelName;
+    /**
+     * 翻译模型配置
+     */
+    private SearchConfig  searchConfig;
+
+
+
+}
--- a/smartjavaai-translate/src/main/java/cn/smartjavaai/translation/config/SearchConfig.java
+++ b/smartjavaai-translate/src/main/java/cn/smartjavaai/translation/config/SearchConfig.java
@@ -0,0 +1,102 @@
+package cn.smartjavaai.translation.config;
+/**
+ * 配置信息
+ * @author lwx
+ * @date 2025/6/05
+ */
+public class SearchConfig {
+
+    private int maxSeqLength;
+    private long padTokenId;
+    private long eosTokenId;
+    private long bosTokenId;
+    private long decoderStartTokenId;
+    private float encoderRepetitionPenalty;
+    private long forcedBosTokenId;
+    private long srcLangId;
+    private float lengthPenalty;
+    public SearchConfig() {
+        this.maxSeqLength = 512;
+        this.eosTokenId = 2;
+        this.bosTokenId = 0;
+        this.padTokenId = 1;
+        this.decoderStartTokenId = 2;
+        this.encoderRepetitionPenalty = 1.0f;
+        this.srcLangId = 0;
+        this.forcedBosTokenId = 0;
+        this.lengthPenalty = 1.0f;
+
+    }
+
+    public long getSrcLangId() {
+        return srcLangId;
+    }
+
+    public void setSrcLangId(long srcLangId) {
+        this.srcLangId = srcLangId;
+    }
+
+    public void setEosTokenId(long eosTokenId) {
+        this.eosTokenId = eosTokenId;
+    }
+
+    public int getMaxSeqLength() {
+        return maxSeqLength;
+    }
+
+    public void setMaxSeqLength(int maxSeqLength) {
+        this.maxSeqLength = maxSeqLength;
+    }
+
+    public long getPadTokenId() {
+        return padTokenId;
+    }
+
+    public void setPadTokenId(long padTokenId) {
+        this.padTokenId = padTokenId;
+    }
+
+    public long getEosTokenId() {
+        return eosTokenId;
+    }
+
+    public long getDecoderStartTokenId() {
+        return decoderStartTokenId;
+    }
+
+    public void setDecoderStartTokenId(long decoderStartTokenId) {
+        this.decoderStartTokenId = decoderStartTokenId;
+    }
+
+    public float getEncoderRepetitionPenalty() {
+        return encoderRepetitionPenalty;
+    }
+
+    public void setEncoderRepetitionPenalty(float encoderRepetitionPenalty) {
+        this.encoderRepetitionPenalty = encoderRepetitionPenalty;
+    }
+
+    public long getForcedBosTokenId() {
+        return forcedBosTokenId;
+    }
+
+    public void setForcedBosTokenId(long forcedBosTokenId) {
+        this.forcedBosTokenId = forcedBosTokenId;
+    }
+
+    public float getLengthPenalty() {
+        return lengthPenalty;
+    }
+
+    public void setLengthPenalty(float lengthPenalty) {
+        this.lengthPenalty = lengthPenalty;
+    }
+
+    public long getBosTokenId() {
+        return bosTokenId;
+    }
+
+    public void setBosTokenId(long bosTokenId) {
+        this.bosTokenId = bosTokenId;
+    }
+}
--- a/smartjavaai-translate/src/main/java/cn/smartjavaai/translation/entity/BatchTensorList.java
+++ b/smartjavaai-translate/src/main/java/cn/smartjavaai/translation/entity/BatchTensorList.java
@@ -0,0 +1,174 @@
+/*
+ * Copyright 2023 Amazon.com, Inc. or its affiliates. All Rights Reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License"). You may not use this file except in compliance
+ * with the License. A copy of the License is located at
+ *
+ * http://aws.amazon.com/apache2.0/
+ *
+ * or in the "license" file accompanying this file. This file is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES
+ * OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions
+ * and limitations under the License.
+ */
+package cn.smartjavaai.translation.entity;
+
+import ai.djl.ndarray.NDArray;
+import ai.djl.ndarray.NDList;
+
+/**
+ * BatchTensorList represents a search state, and the NDArrays inside are updated in each iteration
+ * of the autoregressive loop.
+ *
+ * <p>It is a struct consisting of NDArrays, whose first dimension is batch, and also contains
+ * sequence dimension (whose position in tensor's shape is specified by seqDimOrder). The SeqBatcher
+ * batch operations will operate on these two dimensions.
+ */
+public abstract class BatchTensorList {
+    // [batch, seq_past]. seq-dim-size == |past_seq| + |inputIds|. Will grow.
+    private NDArray pastOutputIds;
+
+    // [batch, seq_past]
+    // The cache of past attentionMask. seq-dim-size == |past_seq| + |inputIds|. Will grow.
+    private NDArray pastAttentionMask;
+
+    // (k, v) * numLayer,
+    // kv: [batch, heads, seq_past, kvfeature]
+    // The cache of past sequence. seq-dim-size == |past_seq| + |inputIds|. Will grow.
+    private NDList pastKeyValues;
+
+    // Sequence dimension order among all dimensions for each element in the batch list.
+    private long[] seqDimOrder;
+
+    BatchTensorList() {}
+
+    /**
+     * Constructs a new {@code BatchTensorList} instance.
+     *
+     * @param list the NDList that contains the serialized version of the batch tensors
+     * @param seqDimOrder the sequence dimension order that specifies where the sequence dimension
+     *     is in a tensor's shape
+     */
+    BatchTensorList(NDList list, long[] seqDimOrder) {
+        this.seqDimOrder = seqDimOrder;
+        pastOutputIds = list.get(0);
+        pastAttentionMask = list.get(1);
+        pastKeyValues = list.subNDList(2);
+    }
+
+    /**
+     * Constructs a new {@code BatchTensorList} instance.
+     *
+     * @param pastOutputIds past output token ids
+     * @param pastAttentionMask past attention mask
+     * @param pastKeyValues past kv cache
+     * @param seqDimOrder the sequence dimension order that specifies where the sequence dimension
+     *     is in a tensor's shape
+     */
+    BatchTensorList(
+            NDArray pastOutputIds,
+            NDArray pastAttentionMask,
+            NDList pastKeyValues,
+            long[] seqDimOrder) {
+        this.pastKeyValues = pastKeyValues;
+        this.pastOutputIds = pastOutputIds;
+        this.pastAttentionMask = pastAttentionMask;
+        this.seqDimOrder = seqDimOrder;
+    }
+
+    /**
+     * Constructs a new {@code BatchTensorList} instance from the serialized version of the batch
+     * tensors.
+     *
+     * <p>The pastOutputIds has to be the first in the output list.
+     *
+     * @param inputList the serialized version of the batch tensors
+     * @param seqDimOrder the sequence dimension order that specifies where the sequence dimension
+     *     is in a tensor's shape
+     * @return BatchTensorList
+     */
+    public abstract BatchTensorList fromList(NDList inputList, long[] seqDimOrder);
+
+    /**
+     * Returns the serialized version of the BatchTensorList. The pastOutputIds has to be the first
+     * in the output list.
+     *
+     * @return the NDList that contains the serialized BatchTensorList
+     */
+    public abstract NDList getList();
+
+    /**
+     * Returns the sequence dimension order which specifies where the sequence dimension is in a
+     * tensor's shape.
+     *
+     * @return the sequence dimension order which specifies where the sequence dimension is in a
+     *     tensor's shape
+     */
+    public long[] getSeqDimOrder() {
+        return seqDimOrder;
+    }
+
+    /**
+     * Returns the value of the pastOutputIds.
+     *
+     * @return the value of pastOutputIds
+     */
+    public NDArray getPastOutputIds() {
+        return pastOutputIds;
+    }
+
+    /**
+     * Sets the past output token ids.
+     *
+     * @param pastOutputIds the past output token ids
+     */
+    public void setPastOutputIds(NDArray pastOutputIds) {
+        this.pastOutputIds = pastOutputIds;
+    }
+
+    /**
+     * Returns the value of the pastAttentionMask.
+     *
+     * @return the value of pastAttentionMask
+     */
+    public NDArray getPastAttentionMask() {
+        return pastAttentionMask;
+    }
+
+    /**
+     * Sets the attention mask.
+     *
+     * @param pastAttentionMask the attention mask
+     */
+    public void setPastAttentionMask(NDArray pastAttentionMask) {
+        this.pastAttentionMask = pastAttentionMask;
+    }
+
+    /**
+     * Returns the value of the pastKeyValues.
+     *
+     * @return the value of pastKeyValues
+     */
+    public NDList getPastKeyValues() {
+        return pastKeyValues;
+    }
+
+    /**
+     * Sets the kv cache.
+     *
+     * @param pastKeyValues the kv cache
+     */
+    public void setPastKeyValues(NDList pastKeyValues) {
+        this.pastKeyValues = pastKeyValues;
+    }
+
+    /**
+     * Sets the sequence dimension order which specifies where the sequence dimension is in a
+     * tensor's shape.
+     *
+     * @param seqDimOrder the sequence dimension order which specifies where the sequence dimension
+     *     is in a tensor's shape
+     */
+    public void setSeqDimOrder(long[] seqDimOrder) {
+        this.seqDimOrder = seqDimOrder;
+    }
+}
--- a/smartjavaai-translate/src/main/java/cn/smartjavaai/translation/entity/CausalLMOutput.java
+++ b/smartjavaai-translate/src/main/java/cn/smartjavaai/translation/entity/CausalLMOutput.java
@@ -0,0 +1,33 @@
+package cn.smartjavaai.translation.entity;
+
+import ai.djl.ndarray.NDArray;
+import ai.djl.ndarray.NDList;
+
+/**
+ * 解码输出对象
+ *
+ * @author Calvin
+ * @mail 179209347@qq.com
+ * @website www.aias.top
+ */
+public class CausalLMOutput {
+    private NDArray logits;
+    private NDList pastKeyValuesList;
+
+    public CausalLMOutput(NDArray logits, NDList pastKeyValues) {
+        this.logits = logits;
+        this.pastKeyValuesList = pastKeyValues;
+    }
+
+    public NDArray getLogits() {
+        return logits;
+    }
+
+    public void setLogits(NDArray logits) {
+        this.logits = logits;
+    }
+
+    public NDList getPastKeyValuesList() {
+        return pastKeyValuesList;
+    }
+}
--- a/smartjavaai-translate/src/main/java/cn/smartjavaai/translation/entity/DirectionInfo.java
+++ b/smartjavaai-translate/src/main/java/cn/smartjavaai/translation/entity/DirectionInfo.java
@@ -0,0 +1,41 @@
+package cn.smartjavaai.translation.entity;
+
+/**
+ * 方向检测结果
+ * @author Calvin
+ * @mail 179209347@qq.com
+ * @website www.aias.top
+ */
+public class DirectionInfo {
+
+    /**
+     * 方向 0 90 180 270
+     */
+    private String name;
+
+    /**
+     * 置信度
+     */
+    private Double prob;
+
+    public DirectionInfo(String name, Double prob) {
+        this.name = name;
+        this.prob = prob;
+    }
+
+    public String getName() {
+        return name;
+    }
+
+    public void setName(String name) {
+        this.name = name;
+    }
+
+    public Double getProb() {
+        return prob;
+    }
+
+    public void setProb(Double prob) {
+        this.prob = prob;
+    }
+}
--- a/smartjavaai-translate/src/main/java/cn/smartjavaai/translation/entity/GreedyBatchTensorList.java
+++ b/smartjavaai-translate/src/main/java/cn/smartjavaai/translation/entity/GreedyBatchTensorList.java
@@ -0,0 +1,84 @@
+package cn.smartjavaai.translation.entity;
+
+import ai.djl.ndarray.NDArray;
+import ai.djl.ndarray.NDList;
+
+/**
+ * 贪婪搜索张量对象列表
+ *
+ * @author Calvin
+ * @mail 179209347@qq.com
+ * @website www.aias.top
+ */
+public class GreedyBatchTensorList extends BatchTensorList {
+    // [batch, 1]
+    private NDArray nextInputIds;
+
+    private NDArray pastOutputIds;
+
+    private NDArray encoderHiddenStates;
+    private NDArray attentionMask;
+    private NDList pastKeyValues;
+
+    public GreedyBatchTensorList(
+            NDArray nextInputIds,
+            NDArray pastOutputIds,
+            NDList pastKeyValues,
+            NDArray encoderHiddenStates,
+            NDArray attentionMask) {
+        this.nextInputIds = nextInputIds;
+        this.pastKeyValues = pastKeyValues;
+        this.pastOutputIds = pastOutputIds;
+        this.attentionMask = attentionMask;
+        this.encoderHiddenStates = encoderHiddenStates;
+    }
+
+    public GreedyBatchTensorList() {}
+
+    public BatchTensorList fromList(NDList inputList, long[] seqDimOrder) {
+        return new GreedyBatchTensorList();
+    }
+
+    public NDList getList() {
+        return new NDList();
+    }
+
+    public NDArray getNextInputIds() {
+        return nextInputIds;
+    }
+
+    public void setNextInputIds(NDArray nextInputIds) {
+        this.nextInputIds = nextInputIds;
+    }
+    public NDArray getPastOutputIds() {
+        return pastOutputIds;
+    }
+
+    public void setPastOutputIds(NDArray pastOutputIds) {
+        this.pastOutputIds = pastOutputIds;
+    }
+
+    public NDList getPastKeyValues() {
+        return pastKeyValues;
+    }
+
+    public void setPastKeyValues(NDList pastKeyValues) {
+        this.pastKeyValues = pastKeyValues;
+    }
+
+    public NDArray getEncoderHiddenStates() {
+        return encoderHiddenStates;
+    }
+
+    public void setEncoderHiddenStates(NDArray encoderHiddenStates) {
+        this.encoderHiddenStates = encoderHiddenStates;
+    }
+
+    public NDArray getAttentionMask() {
+        return attentionMask;
+    }
+
+    public void setAttentionMask(NDArray attentionMask) {
+        this.attentionMask = attentionMask;
+    }
+}
--- a/smartjavaai-translate/src/main/java/cn/smartjavaai/translation/entity/IdCardInfo.java
+++ b/smartjavaai-translate/src/main/java/cn/smartjavaai/translation/entity/IdCardInfo.java
@@ -0,0 +1,12 @@
+package cn.smartjavaai.translation.entity;
+
+/**
+ * 身份证信息
+ * @author dwj
+ * @date 2025/5/22
+ */
+public class IdCardInfo {
+
+
+
+}
--- a/smartjavaai-translate/src/main/java/cn/smartjavaai/translation/enums/MachineTranslationModeEnum.java
+++ b/smartjavaai-translate/src/main/java/cn/smartjavaai/translation/enums/MachineTranslationModeEnum.java
@@ -0,0 +1,23 @@
+package cn.smartjavaai.translation.enums;
+/**
+ * 机器翻译模型枚举
+ * @author lwx
+ * @date 2025/6/05
+ */
+public enum MachineTranslationModeEnum {
+
+    TRACED_TRANSLATION_CPU;
+
+    /**
+     * 根据名称获取枚举 (忽略大小写和下划线变体)
+     */
+    public static MachineTranslationModeEnum fromName(String name) {
+        String formatted = name.trim().toUpperCase().replaceAll("[-_]", "");
+        for (MachineTranslationModeEnum model : values()) {
+            if (model.name().replaceAll("_", "").equals(formatted)) {
+                return model;
+            }
+        }
+        throw new IllegalArgumentException("未知模型名称: " + name);
+    }
+}
--- a/smartjavaai-translate/src/main/java/cn/smartjavaai/translation/exception/TranslationException.java
+++ b/smartjavaai-translate/src/main/java/cn/smartjavaai/translation/exception/TranslationException.java
@@ -0,0 +1,30 @@
+package cn.smartjavaai.translation.exception;
+
+/**
+ * 翻译异常
+ * @author lwx
+ * @date 2025/6/5
+ */
+public class TranslationException extends RuntimeException{
+
+    public TranslationException() {
+        super();
+    }
+
+    public TranslationException(String message, Throwable cause, boolean enableSuppression, boolean writableStackTrace) {
+        super(message, cause, enableSuppression, writableStackTrace);
+    }
+
+    public TranslationException(String message, Throwable cause) {
+        super(message, cause);
+    }
+
+    public TranslationException(String message) {
+        super(message);
+    }
+
+    public TranslationException(Throwable cause) {
+        super(cause);
+    }
+
+}
--- a/smartjavaai-translate/src/main/java/cn/smartjavaai/translation/factory/TranslationModelFactory.java
+++ b/smartjavaai-translate/src/main/java/cn/smartjavaai/translation/factory/TranslationModelFactory.java
@@ -0,0 +1,102 @@
+package cn.smartjavaai.translation.factory;
+
+import cn.smartjavaai.common.config.Config;
+
+
+import cn.smartjavaai.translation.config.MachineTranslationModelConfig;
+import cn.smartjavaai.translation.exception.TranslationException;
+import cn.smartjavaai.translation.model.common.TracedTranslationModel;
+import cn.smartjavaai.translation.model.common.TranslationCommonModel;
+import lombok.extern.slf4j.Slf4j;
+
+import java.util.Map;
+import java.util.Objects;
+import java.util.concurrent.ConcurrentHashMap;
+
+/**
+ * 机器翻译模型工厂
+ * @author dwj
+ */
+@Slf4j
+public class TranslationModelFactory {
+
+    // 使用 volatile 和双重检查锁定来确保线程安全的单例模式
+    private static volatile TranslationModelFactory instance;
+
+    private static final ConcurrentHashMap<String, TranslationCommonModel> commonDetModelMap = new ConcurrentHashMap<>();
+
+
+
+    /**
+     * 检测模型注册表
+     */
+    private static final Map<String, Class<? extends TranslationCommonModel>> commonDetRegistry =
+            new ConcurrentHashMap<>();
+
+
+    public static TranslationModelFactory getInstance() {
+        if (instance == null) {
+            synchronized (TranslationModelFactory.class) {
+                if (instance == null) {
+                    instance = new TranslationModelFactory();
+                }
+            }
+        }
+        return instance;
+    }
+
+
+
+    /**
+     * 注册通用检测模型
+     * @param name
+     * @param clazz
+     */
+    private static void registerCommonDetModel(String name, Class<? extends TranslationCommonModel> clazz) {
+        commonDetRegistry.put(name.toLowerCase(), clazz);
+    }
+
+    /**
+     * 获取检测模型（通过配置）
+     * @param config
+     * @return
+     */
+    public TranslationCommonModel getDetModel(MachineTranslationModelConfig config) {
+        if(Objects.isNull(config) || Objects.isNull(config.getModelEnum())){
+            throw new TranslationException("未配置OCR模型");
+        }
+        return commonDetModelMap.computeIfAbsent(config.getModelEnum().name(), k -> {
+            return createCommonDetModel(config);
+        });
+    }
+
+
+    /**
+     * 创建OCR通用检测模型
+     * @param config
+     * @return
+     */
+    private TranslationCommonModel createCommonDetModel(MachineTranslationModelConfig config) {
+        Class<?> clazz = commonDetRegistry.get(config.getModelEnum().name().toLowerCase());
+        if(clazz == null){
+            throw new TranslationException("Unsupported model");
+        }
+        TranslationCommonModel model = null;
+        try {
+            model = (TranslationCommonModel) clazz.newInstance();
+        } catch (InstantiationException | IllegalAccessException e) {
+            throw new TranslationException(e);
+        }
+        model.loadModel(config);
+        return model;
+    }
+
+
+    // 初始化默认算法
+    static {
+        registerCommonDetModel("TRACED_TRANSLATION_CPU", TracedTranslationModel.class);
+
+        log.info("缓存目录：{}", Config.getCachePath());
+    }
+
+}
--- a/smartjavaai-translate/src/main/java/cn/smartjavaai/translation/model/common/TracedTranslationModel.java
+++ b/smartjavaai-translate/src/main/java/cn/smartjavaai/translation/model/common/TracedTranslationModel.java
@@ -0,0 +1,254 @@
+package cn.smartjavaai.translation.model.common;
+
+import ai.djl.Device;
+import ai.djl.MalformedModelException;
+import ai.djl.engine.Engine;
+import ai.djl.huggingface.tokenizers.Encoding;
+import ai.djl.huggingface.tokenizers.HuggingFaceTokenizer;
+import ai.djl.inference.Predictor;
+import ai.djl.modality.cv.Image;
+import ai.djl.modality.cv.output.DetectedObjects;
+import ai.djl.ndarray.NDArray;
+import ai.djl.ndarray.NDList;
+import ai.djl.ndarray.NDManager;
+import ai.djl.ndarray.index.NDIndex;
+import ai.djl.repository.zoo.Criteria;
+import ai.djl.repository.zoo.ModelNotFoundException;
+import ai.djl.repository.zoo.ModelZoo;
+import ai.djl.repository.zoo.ZooModel;
+import ai.djl.translate.NoopTranslator;
+import ai.djl.translate.TranslateException;
+import cn.smartjavaai.common.config.Config;
+import cn.smartjavaai.common.enums.DeviceEnum;
+import cn.smartjavaai.common.pool.PredictorFactory;
+import cn.smartjavaai.common.pool.ZooModelFactory;
+import cn.smartjavaai.translation.config.MachineTranslationModelConfig;
+import cn.smartjavaai.translation.config.SearchConfig;
+import cn.smartjavaai.translation.entity.CausalLMOutput;
+import cn.smartjavaai.translation.entity.GreedyBatchTensorList;
+import cn.smartjavaai.translation.enums.MachineTranslationModeEnum;
+import cn.smartjavaai.translation.exception.TranslationException;
+import cn.smartjavaai.translation.factory.TranslationModelFactory;
+import cn.smartjavaai.translation.model.common.translator.Decoder2Translator;
+import cn.smartjavaai.translation.model.common.translator.DecoderTranslator;
+import cn.smartjavaai.translation.model.common.translator.EncoderTranslator;
+import cn.smartjavaai.translation.utils.TokenUtils;
+import lombok.extern.slf4j.Slf4j;
+import org.apache.commons.lang3.StringUtils;
+import org.apache.commons.pool2.ObjectPool;
+import org.apache.commons.pool2.impl.GenericObjectPool;
+import org.junit.Test;
+
+import java.io.IOException;
+import java.nio.file.Paths;
+import java.util.Objects;
+
+/**
+ * 机器翻译通用检测模型
+ *
+ * @author lwx
+ * @date 2025/6/05
+ */
+@Slf4j
+public class TracedTranslationModel implements TranslationCommonModel {
+
+    private ObjectPool<ZooModel<NDList, NDList>> detPredictorPool;
+    private ZooModel<NDList, NDList> nllbModel;
+    private HuggingFaceTokenizer tokenizer;
+    private Predictor<long[], NDArray> encoderPredictor;
+    private Predictor<NDList, CausalLMOutput> decoderPredictor;
+    private Predictor<NDList, CausalLMOutput> decoder2Predictor;
+    private SearchConfig searchConfig;
+    private MachineTranslationModelConfig config;
+    private NDManager manager;
+
+    @Test
+    public void detect(){
+        Config.setCachePath("E:\\ai\\models\\libs");
+        MachineTranslationModelConfig config = new MachineTranslationModelConfig();
+        SearchConfig searchConfig = new SearchConfig();
+        // 设置输出文字的最大长度
+        searchConfig.setMaxSeqLength(128);
+        // 设置源语言：中文 "zho_Hans": 256200
+        searchConfig.setSrcLangId(256200);
+        // 设置目标语言：英文 "eng_Latn": 256047
+        searchConfig.setForcedBosTokenId(256047);
+        config.setSearchConfig(searchConfig);
+        config.setDevice(DeviceEnum.CPU);
+        config.setModelEnum(MachineTranslationModeEnum.TRACED_TRANSLATION_CPU);
+        config.setModelPath("E:\\ai\\models\\nlp\\");
+        config.setModelName("traced_translation_cpu.pt");
+        // 输入文字
+        String input2 = "智利北部的丘基卡马塔矿是世界上最大的露天矿之一，长约4公里，宽3公里，深1公里。";
+        String input = "你好，欢迎使用SmartJavaAI！";
+        TranslationCommonModel detModel = TranslationModelFactory.getInstance().getDetModel(config);
+       // detModel.loadModel(config);
+        String translate = detModel.translate(input);
+        System.out.println("识别结果 translate"+translate);
+    }
+    @Override
+    public void loadModel(MachineTranslationModelConfig config) {
+        if (StringUtils.isBlank(config.getModelPath())) {
+            throw new TranslationException("modelPath is null");
+        }
+        Device device = null;
+        if (!Objects.isNull(config.getDevice())) {
+            device = config.getDevice() == DeviceEnum.CPU ? Device.cpu() : Device.gpu();
+        }
+        this.config = config;
+        this.searchConfig = config.getSearchConfig();
+        Criteria<NDList, NDList> criteria =
+                Criteria.builder()
+                        .setTypes(NDList.class, NDList.class)
+                        .optModelPath(Paths.get(config.getModelPath()+config.getModelName()))
+                        .optEngine("PyTorch")
+                        .optDevice(device)
+                        .optTranslator(new NoopTranslator())
+                        .build();
+        try {
+             nllbModel = ModelZoo.loadModel(criteria);
+            // 创建池子：每个线程独享 Predictor
+            this.detPredictorPool = new GenericObjectPool<>(new ZooModelFactory<>(nllbModel));
+            log.info("当前设备: " + nllbModel.getNDManager().getDevice());
+            log.info("当前引擎: " + Engine.getInstance().getEngineName());
+        } catch (IOException | ModelNotFoundException | MalformedModelException e) {
+            throw new TranslationException("模型加载失败", e);
+        }
+    }
+
+    @Override
+    public String translate(String input) throws TranslationException {
+        ZooModel<NDList, NDList> zooModel = null;
+        try (NDManager manager = NDManager.newBaseManager()) {
+            zooModel = detPredictorPool.borrowObject();
+            tokenizer = HuggingFaceTokenizer.newInstance(Paths.get(config.getModelPath() + "tokenizer.json"));
+            encoderPredictor = zooModel.newPredictor(new EncoderTranslator());
+            decoderPredictor = zooModel.newPredictor(new DecoderTranslator());
+            decoder2Predictor = zooModel.newPredictor(new Decoder2Translator());
+            this.manager=manager;
+            return translateLanguage(input);
+        } catch (Exception e) {
+            throw new TranslationException("翻译错误", e);
+        } finally {
+            if (zooModel != null) {
+                try {
+                    detPredictorPool.returnObject(zooModel); //归还
+                } catch (Exception e) {
+                    log.warn("归还Predictor失败", e);
+                    try {
+                        zooModel.close(); // 归还失败才销毁
+                    } catch (Exception ex) {
+                        log.error("关闭Predictor失败", ex);
+                    }
+                }
+            }
+
+        }
+    }
+
+    private String translateLanguage(String input) throws TranslateException {
+
+        Encoding encoding = tokenizer.encode(input);
+        long[] ids = encoding.getIds();
+        // 1. Encoder
+        long[] inputIds = new long[ids.length];
+        // 设置源语言编码
+        inputIds[0] = searchConfig.getSrcLangId();
+        for (int i = 0; i < ids.length - 1; i++) {
+            inputIds[i + 1] = ids[i];
+        }
+
+        long[] attentionMask = encoding.getAttentionMask();
+        NDArray attentionMaskArray = manager.create(attentionMask).expandDims(0);
+
+        NDArray encoderHiddenStates = encoder(inputIds);
+
+        NDArray decoder_input_ids = manager.create(new long[]{searchConfig.getDecoderStartTokenId()}).reshape(1, 1);
+        NDList decoderInput = new NDList(decoder_input_ids, encoderHiddenStates, attentionMaskArray);
+
+        // 2. Initial Decoder
+        CausalLMOutput modelOutput = decoder(decoderInput);
+        modelOutput.getLogits().attach(manager);
+        modelOutput.getPastKeyValuesList().attach(manager);
+
+        GreedyBatchTensorList searchState =
+                new GreedyBatchTensorList(null, decoder_input_ids, modelOutput.getPastKeyValuesList(), encoderHiddenStates, attentionMaskArray);
+
+        while (true) {
+//            try (NDScope ignore = new NDScope()) {
+            NDArray pastOutputIds = searchState.getPastOutputIds();
+
+            if (searchState.getNextInputIds() != null) {
+                decoderInput = new NDList(searchState.getNextInputIds(), searchState.getEncoderHiddenStates(), searchState.getAttentionMask());
+                decoderInput.addAll(searchState.getPastKeyValues());
+                // 3. Decoder loop
+                modelOutput = decoder2(decoderInput);
+            }
+
+            NDArray outputIds = greedyStepGen(searchConfig, pastOutputIds, modelOutput.getLogits());
+
+            searchState.setNextInputIds(outputIds);
+            pastOutputIds = pastOutputIds.concat(outputIds, 1);
+            searchState.setPastOutputIds(pastOutputIds);
+
+            searchState.setPastKeyValues(modelOutput.getPastKeyValuesList());
+
+            long id = searchState.getNextInputIds().toLongArray()[0];
+            if (searchConfig.getEosTokenId() == id) {
+                searchState.setNextInputIds(null);
+                break;
+            }
+            if (searchState.getPastOutputIds() != null && searchState.getPastOutputIds().getShape().get(1) + 1 >= searchConfig.getMaxSeqLength()) {
+                break;
+            }
+        }
+
+        if (searchState.getNextInputIds() == null) {
+            NDArray resultIds = searchState.getPastOutputIds();
+            String result = TokenUtils.decode(searchConfig, tokenizer, resultIds);
+            return result;
+        } else {
+            NDArray resultIds = searchState.getPastOutputIds(); // .concat(searchState.getNextInputIds(), 1)
+            String result = TokenUtils.decode(searchConfig, tokenizer, resultIds);
+            return result;
+        }
+
+    }
+
+    public NDArray greedyStepGen(SearchConfig config, NDArray pastOutputIds, NDArray next_token_scores) {
+        next_token_scores = next_token_scores.get(":, -1, :");
+
+        NDArray new_next_token_scores = manager.create(next_token_scores.getShape(), next_token_scores.getDataType());
+        next_token_scores.copyTo(new_next_token_scores);
+
+        // LogitsProcessor 1. ForcedBOSTokenLogitsProcessor
+        // 设置目标语言
+        long cur_len = pastOutputIds.getShape().getLastDimension();
+        if (cur_len == 1) {
+            long num_tokens = new_next_token_scores.getShape().getLastDimension();
+            for (long i = 0; i < num_tokens; i++) {
+                if (i != config.getForcedBosTokenId()) {
+                    new_next_token_scores.set(new NDIndex(":," + i), Float.NEGATIVE_INFINITY);
+                }
+            }
+            new_next_token_scores.set(new NDIndex(":," + config.getForcedBosTokenId()), 0);
+        }
+
+        NDArray probs = new_next_token_scores.softmax(-1);
+        NDArray next_tokens = probs.argMax(-1);
+
+        return next_tokens.expandDims(0);
+    }
+
+    public NDArray encoder(long[] ids) throws TranslateException {
+        return encoderPredictor.predict(ids);
+    }
+
+    public CausalLMOutput decoder(NDList input) throws TranslateException {
+        return decoderPredictor.predict(input);
+    }
+
+    public CausalLMOutput decoder2(NDList input) throws TranslateException {
+        return decoder2Predictor.predict(input);
+    }
+}
--- a/smartjavaai-translate/src/main/java/cn/smartjavaai/translation/model/common/TranslationCommonModel.java
+++ b/smartjavaai-translate/src/main/java/cn/smartjavaai/translation/model/common/TranslationCommonModel.java
@@ -0,0 +1,32 @@
+package cn.smartjavaai.translation.model.common;
+
+import cn.smartjavaai.translation.config.MachineTranslationModelConfig;
+
+/**
+ * 机器翻译通用检测模型
+ * @author lwx
+ * @date 2025/6/05
+ */
+public interface TranslationCommonModel {
+
+    /**
+     * 加载模型
+     * @param config
+     */
+    void loadModel(MachineTranslationModelConfig config); // 加载模型
+
+    /**
+     * 机器翻译
+     * @param input 翻译内容
+     * @return
+     */
+    default  String translate(String input) {
+        throw new UnsupportedOperationException("默认不支持该功能");
+    }
+
+
+
+
+
+
+}
--- a/smartjavaai-translate/src/main/java/cn/smartjavaai/translation/model/common/translator/Decoder2Translator.java
+++ b/smartjavaai-translate/src/main/java/cn/smartjavaai/translation/model/common/translator/Decoder2Translator.java
@@ -0,0 +1,46 @@
+package cn.smartjavaai.translation.model.common.translator;
+
+import ai.djl.ndarray.NDArray;
+import ai.djl.ndarray.NDList;
+import ai.djl.translate.NoBatchifyTranslator;
+import ai.djl.translate.TranslatorContext;
+import cn.smartjavaai.translation.entity.CausalLMOutput;
+
+
+/**
+ * 解碼器，參數支持 pastKeyValues
+ *
+ * @author Calvin
+ * @mail 179209347@qq.com
+ * @website www.aias.top
+ */
+public class Decoder2Translator implements NoBatchifyTranslator<NDList, CausalLMOutput> {
+    private String tupleName;
+
+    public Decoder2Translator() {
+        tupleName = "past_key_values(" + 12 + ',' + 4 + ')';
+    }
+
+    @Override
+    public NDList processInput(TranslatorContext ctx, NDList input) {
+
+        NDArray placeholder = ctx.getNDManager().create(0);
+        placeholder.setName("module_method:decoder2");
+
+        input.add(placeholder);
+
+        return input;
+    }
+
+    @Override
+    public CausalLMOutput processOutput(TranslatorContext ctx, NDList output) {
+        NDArray logitsOutput = output.get(0);
+        NDList pastKeyValuesOutput = output.subNDList(1, 12 * 4 + 1);
+
+        for (NDArray array : pastKeyValuesOutput) {
+            array.setName(tupleName);
+        }
+
+        return new CausalLMOutput(logitsOutput, pastKeyValuesOutput);
+    }
+}
--- a/smartjavaai-translate/src/main/java/cn/smartjavaai/translation/model/common/translator/DecoderTranslator.java
+++ b/smartjavaai-translate/src/main/java/cn/smartjavaai/translation/model/common/translator/DecoderTranslator.java
@@ -0,0 +1,45 @@
+package cn.smartjavaai.translation.model.common.translator;
+
+import ai.djl.ndarray.NDArray;
+import ai.djl.ndarray.NDList;
+import ai.djl.translate.NoBatchifyTranslator;
+import ai.djl.translate.TranslatorContext;
+import cn.smartjavaai.translation.entity.CausalLMOutput;
+
+/**
+ * 解碼器，參數沒有 pastKeyValues
+ *
+ * @author Calvin
+ * @mail 179209347@qq.com
+ * @website www.aias.top
+ */
+public class DecoderTranslator implements NoBatchifyTranslator<NDList, CausalLMOutput> {
+    private String tupleName;
+
+    public DecoderTranslator() {
+        tupleName = "past_key_values(" + 12 + ',' + 4 + ')';
+    }
+
+    @Override
+    public NDList processInput(TranslatorContext ctx, NDList input) {
+
+        NDArray placeholder = ctx.getNDManager().create(0);
+        placeholder.setName("module_method:decoder");
+
+        input.add(placeholder);
+
+        return input;
+    }
+
+    @Override
+    public CausalLMOutput processOutput(TranslatorContext ctx, NDList output) {
+        NDArray logitsOutput = output.get(0);
+        NDList pastKeyValuesOutput = output.subNDList(1, 12 * 4 + 1);
+
+        for (NDArray array : pastKeyValuesOutput) {
+            array.setName(tupleName);
+        }
+
+        return new CausalLMOutput(logitsOutput, pastKeyValuesOutput);
+    }
+}
--- a/smartjavaai-translate/src/main/java/cn/smartjavaai/translation/model/common/translator/EncoderTranslator.java
+++ b/smartjavaai-translate/src/main/java/cn/smartjavaai/translation/model/common/translator/EncoderTranslator.java
@@ -0,0 +1,49 @@
+package cn.smartjavaai.translation.model.common.translator;
+
+import ai.djl.ndarray.NDArray;
+import ai.djl.ndarray.NDList;
+import ai.djl.ndarray.NDManager;
+import ai.djl.translate.NoBatchifyTranslator;
+import ai.djl.translate.TranslatorContext;
+
+import java.util.Arrays;
+
+/**
+ * 编码器前后处理
+ *
+ * @author Calvin
+ * @mail 179209347@qq.com
+ * @website www.aias.top
+ */
+public class EncoderTranslator implements NoBatchifyTranslator<long[], NDArray> {
+
+
+    public EncoderTranslator() {
+    }
+
+    @Override
+    public NDList processInput(TranslatorContext ctx, long[] input) throws Exception {
+        NDManager manager = ctx.getNDManager();
+
+        NDArray inputIdArray = manager.create(input).expandDims(0);
+        inputIdArray.setName("input_ids");
+
+        long[] attentionMask = new long[input.length];
+        Arrays.fill(attentionMask, 1);
+        NDArray attentionMaskArray = manager.create(attentionMask).expandDims(0);
+        attentionMaskArray.setName("attention_mask");
+
+        NDArray placeholder = ctx.getNDManager().create(0);
+        placeholder.setName("module_method:encoder");
+
+        return new NDList(inputIdArray, attentionMaskArray, placeholder);
+    }
+
+    @Override
+    public NDArray processOutput(TranslatorContext ctx, NDList list) {
+        NDArray encoderHiddenStates = list.get(0);
+        encoderHiddenStates.detach();
+        return encoderHiddenStates;
+    }
+
+}
--- a/smartjavaai-translate/src/main/java/cn/smartjavaai/translation/utils/TokenUtils.java
+++ b/smartjavaai-translate/src/main/java/cn/smartjavaai/translation/utils/TokenUtils.java
@@ -0,0 +1,48 @@
+package cn.smartjavaai.translation.utils;
+
+import ai.djl.huggingface.tokenizers.HuggingFaceTokenizer;
+import ai.djl.ndarray.NDArray;
+import cn.smartjavaai.translation.config.SearchConfig;
+
+
+import java.util.ArrayList;
+
+/**
+ *
+ *
+ * @author lwx
+ * @date 2025/4/22
+ */
+public final class TokenUtils {
+
+    private TokenUtils() {
+    }
+
+    /**
+     * 语言解码
+     *
+     * @param tokenizer
+     * @param output
+     * @return
+     */
+    public static String decode(SearchConfig config, HuggingFaceTokenizer tokenizer, NDArray output) {
+        long[] outputIds = output.toLongArray();
+        ArrayList<Long> outputIdsList = new ArrayList<>();
+
+        for (long id : outputIds) {
+            if (id == config.getEosTokenId() || id==config.getSrcLangId() || id==config.getForcedBosTokenId()) {
+                continue;
+            }
+            outputIdsList.add(id);
+        }
+
+        Long[] objArr =  outputIdsList.toArray(new Long[0]);
+        long[] ids = new long[objArr.length];
+        for (int i = 0; i < objArr.length; i++) {
+            ids[i] = objArr[i];
+        }
+        String text = tokenizer.decode(ids);
+
+        return text;
+    }
+}