Use latest version of the Llama3.java code

Author: geoand

model-providers/llama3-java/runtime/src/main/java/io/quarkiverse/langchain4j/llama3/Llama3ChatModel.java

@@ -96,7 +96,7 @@ public Response<AiMessage> generate(List<ChatMessage> messages) {
 
     private InferenceResponse runInference(Llama model, Sampler sampler, Llama3.Options options,
             List<ChatFormat.Message> messages) {
-        Llama.State state = model.createNewState();
+        Llama.State state = model.createNewState(Llama3.BATCH_SIZE);
         ChatFormat chatFormat = new ChatFormat(model.tokenizer());
 
         List<Integer> promptTokens = new ArrayList<>(chatFormat.encodeDialogPrompt(true, messages));

model-providers/llama3-java/runtime/src/main/java/io/quarkiverse/langchain4j/llama3/Llama3StreamingChatModel.java

@@ -2,6 +2,7 @@
 
 import static dev.langchain4j.data.message.AiMessage.aiMessage;
 import static io.quarkiverse.langchain4j.llama3.MessageMapper.toLlama3Message;
+import static io.quarkiverse.langchain4j.llama3.copy.Llama3.BATCH_SIZE;
 import static io.quarkiverse.langchain4j.llama3.copy.Llama3.selectSampler;
 
 import java.io.IOException;
@@ -84,7 +85,7 @@ public void generate(List<ChatMessage> messages, StreamingResponseHandler<AiMess
     private void runInference(Llama model, Sampler sampler, Llama3.Options options,
             List<ChatFormat.Message> messages,
             StreamingResponseHandler<AiMessage> handler) {
-        Llama.State state = model.createNewState();
+        Llama.State state = model.createNewState(BATCH_SIZE);
         ChatFormat chatFormat = new ChatFormat(model.tokenizer());
 
         List<Integer> promptTokens = new ArrayList<>(chatFormat.encodeDialogPrompt(true, messages));

model-providers/llama3-java/runtime/src/main/java/io/quarkiverse/langchain4j/llama3/copy/AOT.java

@@ -51,7 +51,7 @@ public static PartialModel preLoadGGUF(String modelPath) {
      * No checksum/hash is checked for performance reasons.
      */
     public static Llama tryUsePreLoaded(Path modelPath, int contextLength) throws IOException {
-        PartialModel preLoaded = AOT.PRELOADED_GGUF;
+        AOT.PartialModel preLoaded = AOT.PRELOADED_GGUF;
         if (preLoaded == null) {
             return null; // no pre-loaded model stored
         }

model-providers/llama3-java/runtime/src/main/java/io/quarkiverse/langchain4j/llama3/copy/GGUF.java

@@ -108,7 +108,7 @@ private void loadModelImpl(FileChannel fileChannel) throws IOException {
         // gguf_tensor_info_t tensor_infos[header.tensor_count];
         this.tensorInfos = HashMap.newHashMap(tensorCount);
         for (int i = 0; i < tensorCount; ++i) {
-            GGUFTensorInfo ti = readTensorInfo(fileChannel);
+            GGUF.GGUFTensorInfo ti = readTensorInfo(fileChannel);
             assert !tensorInfos.containsKey(ti.name);
             tensorInfos.put(ti.name, ti);
         }
@@ -156,7 +156,7 @@ private GGMLType readGGMLType(FileChannel fileChannel) throws IOException {
         return GGMLType.fromId(ggmlTypeId);
     }
 
-    private GGUFTensorInfo readTensorInfo(FileChannel fileChannel) throws IOException {
+    private GGUF.GGUFTensorInfo readTensorInfo(FileChannel fileChannel) throws IOException {
         // The name of the tensor. It is a standard GGUF string, with the caveat that
         // it must be at most 64 bytes long.
         String name = readString(fileChannel); // gguf_string_t name;
@@ -180,7 +180,7 @@ private GGUFTensorInfo readTensorInfo(FileChannel fileChannel) throws IOExceptio
         // Must be a multiple of `ALIGNMENT`.
         long offset = readLong(fileChannel); // uint64_t offset;
         assert offset % getAlignment() == 0;
-        return new GGUFTensorInfo(name, dimensions, ggmlType, offset);
+        return new GGUF.GGUFTensorInfo(name, dimensions, ggmlType, offset);
     }
 
     private String readString(FileChannel fileChannel) throws IOException {