kishida

{%- macro render_content(content) %}
    {%- if content is string %}
        {{- content }}
    {%- elif content is iterable and content is not mapping %}
        {%- for item in content %}
            {%- if 'text' in item %}
                {{- item.text }}
            {%- else %}
                {{- raise_exception('Unexpected item type in content.') }}
            {%- endif %}

kishida

diff --git a/ggml/src/ggml-metal/ggml-metal-device.cpp b/ggml/src/ggml-metal/ggml-metal-device.cpp
index c153bd821..64c3d3d70 100644
--- a/ggml/src/ggml-metal/ggml-metal-device.cpp
+++ b/ggml/src/ggml-metal/ggml-metal-device.cpp
@@ -941,6 +941,21 @@ ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_mul_mv(ggml_meta
                 nsg = N_SG_IQ1_M;
                 nr0 = N_R0_IQ1_M;
             } break;
+        case GGML_TYPE_IQ1_XS:
+            {

kishida

#!/usr/bin/env python3
"""
llama.cpp トークナイザー可視化ツール
単一Pythonファイル版 - llama-tokenizeコマンドの結果を色付きで表示
"""

import os
import glob
import subprocess
import json

kishida

import java.util.*;

/**
 * US7680791B2特許の最適化完全実装: Adaptive Quicksort (AQS) v2
 * 
 * 特許の3つの核心技術を完全実装 + 追加最適化:
 * 1. Common Prefix Skipping Quicksort (CPS-QS)
 * 2. Key Substring Caching (2バイト + 拡張オプション)
 * 3. Adaptive Quicksort (Quicksort ↔ Radix Sort 相互再帰)
 * 

kishida

import module java.desktop;

void main() {
    var f = new JFrame("Javaランチャー");
    f.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);
    f.setSize(800, 600);
    f.setLocationRelativeTo(null);
    
    var split = new JSplitPane(JSplitPane.VERTICAL_SPLIT);
    var taSource = new JTextArea();

kishida

package kis;

import module java.desktop;
import module java.base;
import java.net.http.HttpClient;
import java.util.List;

import com.fasterxml.jackson.annotation.JsonIgnore;
import com.fasterxml.jackson.annotation.JsonIgnoreProperties;
import com.fasterxml.jackson.annotation.JsonProperty;

kishida

kishida

import dev.langchain4j.agent.tool.Tool;
import dev.langchain4j.http.client.jdk.JdkHttpClient;
import dev.langchain4j.memory.chat.MessageWindowChatMemory;
import dev.langchain4j.model.openai.OpenAiStreamingChatModel;
import dev.langchain4j.service.AiServices;
import dev.langchain4j.service.TokenStream;
import module java.desktop;
import java.net.http.HttpClient;
import java.time.LocalTime;

kishida

kishida