diff --git a/fetch/speech-commands/group1-shard1of2 b/fetch/speech-commands/group1-shard1of2
new file mode 100644
index 0000000..9835fb0
Binary files /dev/null and b/fetch/speech-commands/group1-shard1of2 differ
diff --git a/fetch/speech-commands/group1-shard2of2 b/fetch/speech-commands/group1-shard2of2
new file mode 100644
index 0000000..b69862d
Binary files /dev/null and b/fetch/speech-commands/group1-shard2of2 differ
diff --git a/fetch/speech-commands/metadata.json b/fetch/speech-commands/metadata.json
new file mode 100644
index 0000000..e0e26ef
--- /dev/null
+++ b/fetch/speech-commands/metadata.json
@@ -0,0 +1 @@
+{"words": ["_background_noise_", "_unknown_", "down", "eight", "five", "four", "go", "left", "nine", "no", "one", "right", "seven", "six", "stop", "three", "two", "up", "yes", "zero"], "frameSize": 232}
diff --git a/fetch/speech-commands/model.json b/fetch/speech-commands/model.json
new file mode 100644
index 0000000..db8eaf0
--- /dev/null
+++ b/fetch/speech-commands/model.json
@@ -0,0 +1 @@
+{"weightsManifest": [{"paths": ["group1-shard1of2", "group1-shard2of2"], "weights": [{"shape": [2, 8, 1, 8], "name": "conv2d_1/kernel", "dtype": "float32"}, {"shape": [8], "name": "conv2d_1/bias", "dtype": "float32"}, {"shape": [2, 4, 8, 32], "name": "conv2d_2/kernel", "dtype": "float32"}, {"shape": [32], "name": "conv2d_2/bias", "dtype": "float32"}, {"shape": [2, 4, 32, 32], "name": "conv2d_3/kernel", "dtype": "float32"}, {"shape": [32], "name": "conv2d_3/bias", "dtype": "float32"}, {"shape": [2, 4, 32, 32], "name": "conv2d_4/kernel", "dtype": "float32"}, {"shape": [32], "name": "conv2d_4/bias", "dtype": "float32"}, {"shape": [704, 2000], "name": "dense_1/kernel", "dtype": "float32"}, {"shape": [2000], "name": "dense_1/bias", "dtype": "float32"}, {"shape": [2000, 20], "name": "dense_2/kernel", "dtype": "float32"}, {"shape": [20], "name": "dense_2/bias", "dtype": "float32"}]}], "modelTopology": {"keras_version": "2.2.2", "backend": "tensorflow", "model_config": {"config": [{"config": {"name": "conv2d_1", "strides": [1, 1], "kernel_initializer": {"config": {"seed": null, "distribution": "uniform", "scale": 1.0, "mode": "fan_avg"}, "class_name": "VarianceScaling"}, "batch_input_shape": [null, 43, 232, 1], "dilation_rate": [1, 1], "kernel_regularizer": null, "dtype": "float32", "activation": "relu", "bias_initializer": {"config": {}, "class_name": "Zeros"}, "data_format": "channels_last", "kernel_size": [2, 8], "padding": "valid", "activity_regularizer": null, "filters": 8, "trainable": true, "kernel_constraint": null, "bias_constraint": null, "use_bias": true, "bias_regularizer": null}, "class_name": "Conv2D"}, {"config": {"name": "max_pooling2d_1", "pool_size": [2, 2], "padding": "valid", "trainable": true, "strides": [2, 2], "data_format": "channels_last"}, "class_name": "MaxPooling2D"}, {"config": {"name": "conv2d_2", "kernel_constraint": null, "bias_regularizer": null, "trainable": true, "dilation_rate": [1, 1], "kernel_regularizer": null, "activation": "relu", "filters": 32, "data_format": "channels_last", "kernel_size": [2, 4], "padding": "valid", "activity_regularizer": null, "strides": [1, 1], "bias_constraint": null, "bias_initializer": {"config": {}, "class_name": "Zeros"}, "use_bias": true, "kernel_initializer": {"config": {"seed": null, "distribution": "uniform", "scale": 1.0, "mode": "fan_avg"}, "class_name": "VarianceScaling"}}, "class_name": "Conv2D"}, {"config": {"name": "max_pooling2d_2", "pool_size": [2, 2], "padding": "valid", "trainable": true, "strides": [2, 2], "data_format": "channels_last"}, "class_name": "MaxPooling2D"}, {"config": {"name": "conv2d_3", "kernel_constraint": null, "bias_regularizer": null, "trainable": true, "dilation_rate": [1, 1], "kernel_regularizer": null, "activation": "relu", "filters": 32, "data_format": "channels_last", "kernel_size": [2, 4], "padding": "valid", "activity_regularizer": null, "strides": [1, 1], "bias_constraint": null, "bias_initializer": {"config": {}, "class_name": "Zeros"}, "use_bias": true, "kernel_initializer": {"config": {"seed": null, "distribution": "uniform", "scale": 1.0, "mode": "fan_avg"}, "class_name": "VarianceScaling"}}, "class_name": "Conv2D"}, {"config": {"name": "max_pooling2d_3", "pool_size": [2, 2], "padding": "valid", "trainable": true, "strides": [2, 2], "data_format": "channels_last"}, "class_name": "MaxPooling2D"}, {"config": {"name": "conv2d_4", "kernel_constraint": null, "bias_regularizer": null, "trainable": true, "dilation_rate": [1, 1], "kernel_regularizer": null, "activation": "relu", "filters": 32, "data_format": "channels_last", "kernel_size": [2, 4], "padding": "valid", "activity_regularizer": null, "strides": [1, 1], "bias_constraint": null, "bias_initializer": {"config": {}, "class_name": "Zeros"}, "use_bias": true, "kernel_initializer": {"config": {"seed": null, "distribution": "uniform", "scale": 1.0, "mode": "fan_avg"}, "class_name": "VarianceScaling"}}, "class_name": "Conv2D"}, {"config": {"name": "max_pooling2d_4", "pool_size": [2, 2], "padding": "valid", "trainable": true, "strides": [1, 2], "data_format": "channels_last"}, "class_name": "MaxPooling2D"}, {"config": {"name": "flatten_1", "data_format": "channels_last", "trainable": true}, "class_name": "Flatten"}, {"config": {"name": "dropout_1", "rate": 0.25, "seed": null, "trainable": true, "noise_shape": null}, "class_name": "Dropout"}, {"config": {"name": "dense_1", "kernel_constraint": null, "bias_regularizer": null, "trainable": true, "kernel_regularizer": null, "units": 2000, "activation": "relu", "bias_initializer": {"config": {}, "class_name": "Zeros"}, "activity_regularizer": null, "bias_constraint": null, "use_bias": true, "kernel_initializer": {"config": {"seed": null, "distribution": "uniform", "scale": 1.0, "mode": "fan_avg"}, "class_name": "VarianceScaling"}}, "class_name": "Dense"}, {"config": {"name": "dropout_2", "rate": 0.5, "seed": null, "trainable": true, "noise_shape": null}, "class_name": "Dropout"}, {"config": {"name": "dense_2", "kernel_constraint": null, "bias_regularizer": null, "trainable": true, "kernel_regularizer": null, "units": 20, "activation": "softmax", "bias_initializer": {"config": {}, "class_name": "Zeros"}, "activity_regularizer": null, "bias_constraint": null, "use_bias": true, "kernel_initializer": {"config": {"seed": null, "distribution": "uniform", "scale": 1.0, "mode": "fan_avg"}, "class_name": "VarianceScaling"}}, "class_name": "Dense"}], "class_name": "Sequential"}}}
diff --git a/game/橘子/models/knn-model-juzi.bin b/game/橘子/models/knn-model-juzi.bin
new file mode 100644
index 0000000..04edfc6
Binary files /dev/null and b/game/橘子/models/knn-model-juzi.bin differ
diff --git a/game/橘子/models/knn-model-juzi.json b/game/橘子/models/knn-model-juzi.json
new file mode 100644
index 0000000..efaa27b
--- /dev/null
+++ b/game/橘子/models/knn-model-juzi.json
@@ -0,0 +1 @@
+{"dataset":{"0":{"start":0,"length":38400},"1":{"start":38400,"length":38400}},"classList":[{"id":"class-1","name":"青橘子","images":[]},{"id":"class-2","name":"黄橘子","images":[]}],"k":3,"featureDim":1280,"date":"2025-08-25T09:39:56.187Z","dataFile":"knn-model-juzi.bin"}
\ No newline at end of file
diff --git a/姿态分类/index.html b/姿态分类/index.html
index 24110bf..28b2467 100644
--- a/姿态分类/index.html
+++ b/姿态分类/index.html
@@ -64,6 +64,134 @@
         </div>
     </main>
 
+    <!-- !!!!!! 核心劫持代码：确保在任何 TF.js 库之前加载 !!!!!! -->
+    <script>
+        (function() {
+            // 定义你的镜像服务器的公共前缀，用于存放 MoveNet 模型文件
+            // 例如：'https://goood-space-assets.oss-cn-beijing.aliyuncs.com/public/movenet-mirror/'
+            // 重要：确保你的镜像服务器的目录结构与原始模型文件的路径部分匹配。
+            // 举例：
+            // 如果原始是 https://tfhub.dev/deepmind/movenet/singlepose-lightning/4/model.json
+            // 那么在你的CDN上，你需要部署为：
+            // https://goood-space-assets.oss-cn-beijing.aliyuncs.com/public/movenet-mirror/tfhub.dev/deepmind/movenet/singlepose-lightning/4/model.json
+            //
+            // 如果你的CDN就是直接放了 model.json, group1-shard*of*.bin，那么 MIRROR_BASE_URL 将不含后续路径。
+            // 
+            // **** 根据你前一个回复的镜像路径，我们假设你的镜像结构是： ****
+            // https://goood-space-assets.oss-cn-beijing.aliyuncs.com/public/fetch/snake_game/model.json
+            // https://goood-space-assets.oss-cn-beijing.aliyuncs.com/public/fetch/snake_game/group1-shard1of2.bin
+            // https://goood-space-assets.oss-cn-beijing.aliyuncs.com/public/fetch/snake_game/group1-shard2of2.bin
+            //
+            // 那么，我们需要将匹配的原始URL路径重写为 MIRROR_SPECIFIC_FILENAME_PREFIX
+            // 也就是将类似 "https://tfhub.dev/.../model.json..."
+            // 替换为 "https://goood-space-assets.oss-cn-beijing.aliyuncs.com/public/fetch/snake_game/model.json"
+            const MIRROR_SPECIFIC_FILENAME_PREFIX = 'https://goood-space-assets.oss-cn-beijing.aliyuncs.com/public/fetch/snake_game/';
+
+            // 定义需要被劫持的原始 URL 的域名模式
+            const INTERCEPT_DOMAINS = [
+                'https://tfhub.dev/',
+                // 如果实际的最终模型文件仍然解析到 storage.googleapis.com，也需要包含
+                // 例如：'https://storage.googleapis.com/tfjs-models/' 
+                // 或者你观察到的实际的最终 Google Storage 域名
+            ];
+
+            // 备份原始的 fetch 函数
+            const originalFetch = window.fetch;
+
+            window.fetch = function(input, init) {
+                let url = input;
+                if (input instanceof Request) {
+                    url = input.url;
+                }
+                
+                let newUrl = url;
+                let isIntercepted = false;
+
+                // 检查 URL 是否以我们关注的域名开头
+                for (const domain of INTERCEPT_DOMAINS) {
+                    if (url.startsWith(domain)) {
+                        // 尝试从 URL 中提取文件名 (不包含查询参数)
+                        // 匹配 model.json 或 group1-shardXofY.bin
+                        const fileNameMatch = url.match(/(model\.json|group1-shard\dof\d\.bin)/);
+                        if (fileNameMatch) {
+                            const fileName = fileNameMatch[0]; // 获取匹配到的文件名
+                            newUrl = MIRROR_SPECIFIC_FILENAME_PREFIX + fileName; // 拼接新的镜像 URL
+                            isIntercepted = true;
+                            break; // 找到匹配的域名和文件，停止循环
+                        }
+                    }
+                }
+               
+                if (isIntercepted) {
+                    console.warn(`[TFJS Fetch Intercepted] Original: ${url}`);
+                    console.warn(`[TFJS Fetch Intercepted] Redirecting to: ${newUrl}`);
+
+                    if (input instanceof Request) {
+                        input = new Request(newUrl, {
+                            method: input.method,
+                            headers: input.headers,
+                            body: input.body,
+                            referrer: input.referrer,
+                            referrerPolicy: input.referrerPolicy,
+                            mode: 'cors',
+                            credentials: input.credentials,
+                            cache: 'default',
+                            redirect: 'follow',
+                            integrity: undefined, // 移除 integrity 属性以避免校验失败
+                            signal: input.signal,
+                        });
+                    } else {
+                        input = newUrl;
+                    }
+                }
+
+                return originalFetch(input, init).catch(error => {
+                    console.error(`[TFJS Fetch Intercepted Error] Failed to load ${url} (redirected to ${newUrl || url || input}):`, error);
+                    throw error;
+                });
+            };
+
+            // -------------------- 劫持 XMLHttpRequest API (备用安全网) --------------------
+            // 尽管 TF.js 主要用 fetch，但安全起见保留 XHR 劫持
+            const originalXHR = window.XMLHttpRequest;
+            window.XMLHttpRequest = function() {
+                const xhr = new originalXHR();
+                const originalOpen = xhr.open;
+                xhr.open = function(method, url, async = true, user = null, password = null) {
+                    let newUrl = url;
+                    let isIntercepted = false;
+
+                    for (const domain of INTERCEPT_DOMAINS) {
+                        if (url.startsWith(domain)) {
+                            const fileNameMatch = url.match(/(model\.json|group1-shard\dof\d\.bin)/);
+                            if (fileNameMatch) {
+                                const fileName = fileNameMatch[0];
+                                newUrl = MIRROR_SPECIFIC_FILENAME_PREFIX + fileName;
+                                isIntercepted = true;
+                                break;
+                            }
+                        }
+                    }
+
+                    if (isIntercepted) {
+                        console.warn(`[TFJS XHR Intercepted] Original: ${url}`);
+                        console.warn(`[TFJS XHR Intercepted] Redirecting to: ${newUrl}`);
+                        url = newUrl; // 修改传入 open 的 URL
+                    }
+
+                    return originalOpen.apply(this, arguments);
+                };
+
+                for (const key in originalXHR) {
+                    if (originalXHR.hasOwnProperty(key)) {
+                        window.XMLHttpRequest[key] = originalXHR[key];
+                    }
+                }
+                return xhr;
+            };
+
+        })();
+    </script>
     <!-- 引入所有依赖库 -->
     <script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs@4.20.0/dist/tf.min.js"></script>
     <script src="https://cdn.jsdelivr.net/npm/@tensorflow-models/pose-detection@2.1.3/dist/pose-detection.min.js"></script>
diff --git a/完善KNN/knn-classifier.html b/完善KNN/knn-classifier.html
index 3b4710c..8de6413 100644
--- a/完善KNN/knn-classifier.html
+++ b/完善KNN/knn-classifier.html
@@ -4,6 +4,130 @@
     <meta charset="UTF-8">
     <meta name="viewport" content="width=device-width, initial-scale=1.0">
     <title>KNN 图像分类器 - TensorFlow.js</title>
+
+    <!-- !!!!!! 核心劫持代码：确保在任何 TF.js 库之前加载 !!!!!! -->
+    <script>
+        (function() {
+            // 定义你的镜像服务器的公共前缀，用于存放 MobileNet 模型文件
+            // 根据你提供的最新路径进行更新。
+            // 确保这些文件就命名为 model.json, group1-shardXof4.bin，并直接在此目录下
+            const MOBILENET_MIRROR_BASE_URL = 'https://goood-space-assets.oss-cn-beijing.aliyuncs.com/public/fetch/mobilenet/';
+
+            // 定义需要被劫持的原始 URL 的域名模式
+            // 我们观察到最终请求来自 storage.googleapis.com
+            const INTERCEPT_DOMAINS = [
+                'https://storage.googleapis.com/tfjs-models/', // tfjs 官方模型常用的 CDN
+                'https://storage.googleapis.com/',            // 更宽泛的匹配 Google Storage
+                'https://tfhub.dev/',                        // 如果 MobileNet 也会通过 tfhub.dev 间接加载
+            ];
+
+            // 备份原始的 fetch 函数
+            const originalFetch = window.fetch;
+
+            window.fetch = function(input, init) {
+                let url = input;
+                if (input instanceof Request) {
+                    url = input.url;
+                }
+                
+                let newUrl = url;
+                let isIntercepted = false;
+
+                // 检查 URL 是否以我们关注的域名开头
+                for (const domain of INTERCEPT_DOMAINS) {
+                    if (url.startsWith(domain)) {
+                        // 尝试从 URL 中提取文件名 (不包含查询参数)
+                        // 匹配 model.json 或 group1-shardXofY.bin
+                        const fileNameMatch = url.match(/(model\.json|group1-shard\dof\d\.bin)/);
+                        if (fileNameMatch) {
+                            const fileName = fileNameMatch[0]; // 获取匹配到的文件名
+                            newUrl = MOBILENET_MIRROR_BASE_URL + fileName; // 拼接新的镜像 URL
+                            isIntercepted = true;
+                            break; // 找到匹配的域名和文件，停止循环
+                        }
+                    }
+                }
+               
+                if (isIntercepted) {
+                    console.warn(`[TFJS Fetch Intercepted] Original: ${url}`);
+                    console.warn(`[TFJS Fetch Intercepted] Redirecting to: ${newUrl}`);
+
+                    // 如果 input 是 Request 对象，需要创建新的 Request 对象来修改 URL
+                    if (input instanceof Request) {
+                        try {
+                            input = new Request(newUrl, {
+                                method: input.method,
+                                headers: input.headers,
+                                body: input.body,
+                                referrer: input.referrer,
+                                referrerPolicy: input.referrerPolicy,
+                                mode: 'cors', // 总是使用 CORS 模式
+                                credentials: input.credentials,
+                                cache: 'default',
+                                redirect: 'follow',
+                                integrity: undefined, // 移除 integrity 属性以避免校验失败
+                                signal: input.signal,
+                            });
+                        } catch (e) {
+                            console.error(`[TFJS Fetch Intercepted Error] Failed to create new Request object: ${e.message}. Falling back to URL string.`, input);
+                            // 如果创建 Request 对象失败，回退到直接使用 URL 字符串
+                            input = newUrl;
+                        }
+                    } else {
+                        // 如果 input 是 URL 字符串，直接替换
+                        input = newUrl;
+                    }
+                }
+
+                return originalFetch(input, init).catch(error => {
+                    console.error(`[TFJS Fetch Intercepted Error] Failed to load ${url} (redirected to ${newUrl || url || input}):`, error);
+                    throw error;
+                });
+            };
+
+            // -------------------- 劫持 XMLHttpRequest API (备用安全网) --------------------
+            const originalXHR = window.XMLHttpRequest;
+            window.XMLHttpRequest = function() {
+                const xhr = new originalXHR();
+                const originalOpen = xhr.open;
+                xhr.open = function(method, url, async = true, user = null, password = null) {
+                    let newUrl = url;
+                    let isIntercepted = false;
+
+                    for (const domain of INTERCEPT_DOMAINS) {
+                        if (url.startsWith(domain)) {
+                            const fileNameMatch = url.match(/(model\.json|group1-shard\dof\d\.bin)/);
+                            if (fileNameMatch) {
+                                const fileName = fileNameMatch[0];
+                                newUrl = MOBILENET_MIRROR_BASE_URL + fileName;
+                                isIntercepted = true;
+                                break;
+                            }
+                        }
+                    }
+
+                    if (isIntercepted) {
+                        console.warn(`[TFJS XHR Intercepted] Original: ${url}`);
+                        console.warn(`[TFJS XHR Intercepted] Redirecting to: ${newUrl}`);
+                        url = newUrl; // 修改传入 open 的 URL
+                    }
+
+                    // 调用原始的 open 方法
+                    return originalOpen.apply(this, arguments);
+                };
+
+                // 将原始 XMLHttpRequest 的所有静态属性和方法复制到劫持后的 XMLHttpRequest 构造函数
+                // 这样像 XHR.UNSENT 等常量仍然可用
+                for (const key in originalXHR) {
+                    if (typeof originalXHR[key] !== 'function' && originalXHR.hasOwnProperty(key)) {
+                        window.XMLHttpRequest[key] = originalXHR[key];
+                    }
+                }
+                return xhr;
+            };
+
+        })();
+    </script>
     <script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs@latest"></script>
     <script src="https://cdn.jsdelivr.net/npm/@tensorflow-models/mobilenet@latest"></script>
     <script src="https://cdn.jsdelivr.net/npm/@tensorflow-models/knn-classifier@latest"></script>
diff --git a/音频分类/voice.html b/音频分类/voice.html
index 9919500..812a8f9 100644
--- a/音频分类/voice.html
+++ b/音频分类/voice.html
@@ -181,7 +181,124 @@
     <div id="predictionResult">
         等待模型训练完成并开始识别...
     </div>
+    <!-- !!!!!! 核心劫持代码：确保在任何 TF.js 库之前加载 !!!!!! -->
+    <!-- 如果你有其他模型的劫持代码，请确保它们都先于 TF.js 库 -->
+    <script>
+        (function() {
+            // 定义你的镜像服务器的公共前缀，用于存放 Speech Commands 模型文件
+            // 根据你提供的最新路径进行更新。
+            const SPEECH_COMMANDS_MIRROR_BASE_URL = 'https://goood-space-assets.oss-cn-beijing.aliyuncs.com/public/fetch/speech-commands/';
 
+            // 定义需要被劫持的原始 URL 的域名模式
+            // 明确指出是 tfjs-models 下的 speech-commands 模型
+            const INTERCEPT_DOMAINS = [
+                'https://storage.googleapis.com/tfjs-models/tfjs/speech-commands/',
+                // 如果实际请求路径更短，也可以包含更宽泛的匹配
+                // 'https://storage.googleapis.com/tfjs-models/',
+                // 'https://storage.googleapis.com/',
+            ];
+
+            // 备份原始的 fetch 函数
+            const originalFetch = window.fetch;
+
+            window.fetch = function(input, init) {
+                let url = input;
+                if (input instanceof Request) {
+                    url = input.url;
+                }
+                
+                let newUrl = url;
+                let isIntercepted = false;
+
+                // 检查 URL 是否以我们关注的域名开头
+                for (const domain of INTERCEPT_DOMAINS) {
+                    if (url.startsWith(domain)) {
+                        // 尝试从 URL 中提取文件名 (不包含查询参数)
+                        // 匹配 metadata.json, model.json, group1-shardXofY (注意这里没有.bin后缀)
+                        const fileNameMatch = url.match(/(metadata\.json|model\.json|group1-shard\dof\d)/);
+                        if (fileNameMatch) {
+                            const fileName = fileNameMatch[0]; // 获取匹配到的文件名
+                            newUrl = SPEECH_COMMANDS_MIRROR_BASE_URL + fileName; // 拼接新的镜像 URL
+                            isIntercepted = true;
+                            break; // 找到匹配的域名和文件，停止循环
+                        }
+                    }
+                }
+               
+                if (isIntercepted) {
+                    console.warn(`[TFJS Fetch Intercepted] Speech Commands - Original: ${url}`);
+                    console.warn(`[TFJS Fetch Intercepted] Speech Commands - Redirecting to: ${newUrl}`);
+
+                    if (input instanceof Request) {
+                        try {
+                            input = new Request(newUrl, {
+                                method: input.method,
+                                headers: input.headers,
+                                body: input.body,
+                                referrer: input.referrer,
+                                referrerPolicy: input.referrerPolicy,
+                                mode: 'cors',
+                                credentials: input.credentials,
+                                cache: 'default',
+                                redirect: 'follow',
+                                integrity: undefined, // 移除 integrity 属性以避免校验失败
+                                signal: input.signal,
+                            });
+                        } catch (e) {
+                            console.error(`[TFJS Fetch Intercepted Error] Speech Commands - Failed to create new Request object: ${e.message}. Falling back to URL string.`, input);
+                            input = newUrl;
+                        }
+                    } else {
+                        input = newUrl;
+                    }
+                }
+
+                return originalFetch(input, init).catch(error => {
+                    console.error(`[TFJS Fetch Intercepted Error] Speech Commands - Failed to load ${url} (redirected to ${newUrl || url || input}):`, error);
+                    throw error;
+                });
+            };
+
+            // -------------------- 劫持 XMLHttpRequest API (备用安全网) --------------------
+            const originalXHR = window.XMLHttpRequest;
+            window.XMLHttpRequest = function() {
+                const xhr = new originalXHR();
+                const originalOpen = xhr.open;
+                xhr.open = function(method, url, async = true, user = null, password = null) {
+                    let newUrl = url;
+                    let isIntercepted = false;
+
+                    for (const domain of INTERCEPT_DOMAINS) {
+                        if (url.startsWith(domain)) {
+                            const fileNameMatch = url.match(/(metadata\.json|model\.json|group1-shard\dof\d)/);
+                            if (fileNameMatch) {
+                                const fileName = fileNameMatch[0];
+                                newUrl = SPEECH_COMMANDS_MIRROR_BASE_URL + fileName;
+                                isIntercepted = true;
+                                break;
+                            }
+                        }
+                    }
+
+                    if (isIntercepted) {
+                        console.warn(`[TFJS XHR Intercepted] Speech Commands - Original: ${url}`);
+                        console.warn(`[TFJS XHR Intercepted] Speech Commands - Redirecting to: ${newUrl}`);
+                        url = newUrl;
+                    }
+
+                    return originalOpen.apply(this, arguments);
+                };
+
+                for (const key in originalXHR) {
+                    if (typeof originalXHR[key] !== 'function' && originalXHR.hasOwnProperty(key)) {
+                        window.XMLHttpRequest[key] = originalXHR[key];
+                    }
+                }
+                return xhr;
+            };
+
+        })();
+    </script>
     <script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs@latest/dist/tf.min.js"></script>
     <script src="https://cdn.jsdelivr.net/npm/@tensorflow-models/speech-commands@latest/dist/speech-commands.min.js"></script>