update:test迁移重命名为digital-human
3030332422
@@ -1,8 +1,8 @@
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# Test 页面语音唤醒
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# 数字人唤醒词教程
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## 概述
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Test 页面集成了基于 **Sherpa-ONNX** 的高精度语音唤醒功能，支持自定义唤醒词和实时检测。使用轻量级关键词检测模型，提供毫秒级响应速度。
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测试页面集成了基于 **Sherpa-ONNX** 的高精度语音唤醒功能，支持自定义唤醒词和实时检测。使用轻量级关键词检测模型，提供毫秒级响应速度。
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## 唤醒词模型
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@@ -21,7 +21,7 @@ Test 页面集成了基于 **Sherpa-ONNX** 的高精度语音唤醒功能，支
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```bash
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# 方法1：直接下载（推荐）
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cd main/xiaozhi-server/test/wakeword_runtime/
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cd main/digital-human/wakeword_runtime/
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wget https://github.com/k2-fsa/sherpa-onnx/releases/download/kws-models/sherpa-onnx-kws-zipformer-wenetspeech-3.3M-2024-01-01.tar.bz2
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# 解压
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@@ -42,13 +42,13 @@ snapshot_download('pkufool/sherpa-onnx-kws-zipformer-wenetspeech-3.3M-2024-01-01
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```
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sherpa-onnx-kws-zipformer-wenetspeech-3.3M-2024-01-01/
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├── encoder-epoch-12-avg-2-chunk-16-left-64.int8.onnx # 速度优先
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├── encoder-epoch-12-avg-2-chunk-16-left-64.onnx #
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├── encoder-epoch-12-avg-2-chunk-16-left-64.onnx
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├── encoder-epoch-99-avg-1-chunk-16-left-64.int8.onnx # 速度优先
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├── encoder-epoch-99-avg-1-chunk-16-left-64.onnx # 精度优先
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├── decoder-epoch-12-avg-2-chunk-16-left-64.onnx #
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├── decoder-epoch-12-avg-2-chunk-16-left-64.onnx
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├── decoder-epoch-99-avg-1-chunk-16-left-64.onnx # 精度优先
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├── joiner-epoch-12-avg-2-chunk-16-left-64.int8.onnx # 速度优先
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├── joiner-epoch-12-avg-2-chunk-16-left-64.onnx #
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├── joiner-epoch-12-avg-2-chunk-16-left-64.onnx
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├── joiner-epoch-99-avg-1-chunk-16-left-64.int8.onnx # 速度优先
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├── joiner-epoch-99-avg-1-chunk-16-left-64.onnx # 精度优先
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├── tokens.txt # Token映射表（必需）
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@@ -76,7 +76,7 @@ cp joiner-epoch-99-avg-1-chunk-16-left-64.onnx ../models/joiner.onnx
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# 复制配套文件
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cp tokens.txt ../models/tokens.txt
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# keywords_raw.txt 如果模型包里附带，可自行保留；test runtime 不依赖它
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# keywords_raw.txt 如果模型包里附带，可自行保留；runtime 不依赖它
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```
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**方案二：速度优先**
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@@ -98,36 +98,36 @@ cp tokens.txt ../models/tokens.txt
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**注意事项**:
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- **不要混用fp32与int8**：三个模型文件必须保持一致的精度
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- **优先选择epoch-99**：比epoch-12训练更充分，精度更高
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- **不要混用 fp32 与 int8**：三个模型文件必须保持一致的精度
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- **优先选择 epoch-99**：比 epoch-12 训练更充分，精度更高
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- **必需文件**：`encoder.onnx` + `decoder.onnx` + `joiner.onnx` + `tokens.txt` + `keywords.txt`
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### 最终模型文件结构
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配置完成后，模型文件应放在 `wakeword_runtime/models/` 目录下（完整路径：`main/xiaozhi-server/test/wakeword_runtime/models/`）：
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配置完成后，模型文件应放在 `wakeword_runtime/models/` 目录下，完整路径为 `main/digital-human/wakeword_runtime/models/`：
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```
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wakeword_runtime/models/
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├── encoder.onnx # 编码器模型（重命名后）
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├── decoder.onnx # 解码器模型（重命名后）
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├── joiner.onnx # 连接器模型（重命名后）
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├── tokens.txt # 拼音Token映射表（228行版本）
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├── tokens.txt # 拼音 Token 映射表（228行版本）
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├── keywords.txt # 关键词配置文件（首次启动自动生成）
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└── keywords_raw.txt # 可选，runtime 不依赖
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```
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## 启动方式
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在 `main/xiaozhi-server/test` 目录执行：
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在 `main/digital-human` 目录执行：
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```bash
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pip install -r wakeword_runtime/requirements.txt
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python start_test_runtime.py
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python start.py
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```
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启动后默认地址：
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- 页面地址：`http://127.0.0.1:8006/test_page.html`
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- 页面地址：`http://127.0.0.1:8006/index.html`
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- 事件桥地址：`ws://127.0.0.1:8006/wakeword-ws`
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- 健康检查：`http://127.0.0.1:8006/health`
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@@ -136,38 +136,37 @@ python start_test_runtime.py
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- 在运行终端按 `Ctrl+C`
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- 会同时停止静态页面服务、事件桥和唤醒词检测流程
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## 配置文件说明
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配置文件位于 [config.json](./config.json)。
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配置文件位于 [main/digital-human/wakeword_runtime/config.json](../main/digital-human/wakeword_runtime/config.json)。
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当前主要配置项：
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```json
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{
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"wakeword": {
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"enabled": true
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},
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"model_dir": "models",
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"audio": {
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"input_device": null,
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"sample_rate": 16000,
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"channels": 1
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},
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"detector": {
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"num_threads": 4,
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"provider": "cpu",
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"max_active_paths": 2,
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"keywords_score": 1.8,
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"keywords_threshold": 0.1,
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"num_trailing_blanks": 1,
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"cooldown_seconds": 1.5
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},
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"logging": {
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"level": "INFO",
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"dir": "logs",
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"file": "wakeword-runtime.log"
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}
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"wakeword": {
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"enabled": true
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},
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"model_dir": "models",
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"audio": {
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"input_device": null,
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"sample_rate": 16000,
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"channels": 1
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},
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"detector": {
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"num_threads": 4,
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"provider": "cpu",
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"max_active_paths": 2,
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"keywords_score": 1.8,
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"keywords_threshold": 0.1,
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"num_trailing_blanks": 1,
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"cooldown_seconds": 1.5
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},
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"logging": {
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"level": "INFO",
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"dir": "logs",
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"file": "wakeword-runtime.log"
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}
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}
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```
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@@ -197,13 +196,13 @@ python start_test_runtime.py
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1. 准备 `models/` 目录下的模型文件和 `tokens.txt`
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2. 确认 `models/keywords.txt` 存在
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3. 在 `test` 目录运行 `python start_test_runtime.py`
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4. 浏览器打开 `http://127.0.0.1:8006/test_page.html`
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3. 在 `digital-human` 目录运行 `python start.py`
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4. 浏览器打开 `http://127.0.0.1:8006/index.html`
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5. 进入设置页检查“唤醒词”配置
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### 修改唤醒词
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1. 打开 test 页面设置
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1. 打开数字人页面设置
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2. 切到“唤醒词”页签
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3. 修改启用状态或唤醒词列表
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4. 点击“应用唤醒词”
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@@ -0,0 +1,41 @@
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本文档是开发类文档，如需部署小智服务端，[点击这里查看部署教程](../../README.md#%E9%83%A8%E7%BD%B2%E6%96%87%E6%A1%A3)
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如需查看唤醒词模型下载、运行时配置和详细使用说明，[点击这里查看专题文档](../../docs/digital-human-wakeword.md)
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# 项目介绍
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digital-human 是独立的数字人测试模块，负责提供本地测试页面、前端交互资源、唤醒词运行时和事件桥能力，用于联调整个数字人交互链路。
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# 快速启动
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安装依赖：
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```bash
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pip install -r wakeword_runtime/requirements.txt
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```
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启动模块：
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```bash
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python start.py
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```
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# 访问地址
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启动后可访问：
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- 页面地址：http://127.0.0.1:8006/index.html
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- 事件桥地址：ws://127.0.0.1:8006/wakeword-ws
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- 健康检查：http://127.0.0.1:8006/health
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# 目录说明
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- `start.py`：模块启动入口
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- `index.html`：数字人测试页面入口
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- `wakeword_runtime`：本地唤醒词运行时与配置目录
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- `js`、`css`：页面前端脚本与样式
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- `images`、`resources`：页面资源文件
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# 相关文档
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唤醒词专题文档：[../../docs/digital-human-wakeword.md](../../docs/digital-human-wakeword.md)
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@@ -24,11 +24,11 @@
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<p>您可以使用nginx映射启动测试页面，也可以请按照以下步骤启动测试运行时：</p>
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<ol>
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<li>打开命令行终端</li>
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<li>命令行进入到 xiaozhi-server/test 目录</li>
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<li>命令行进入到 digital-human 目录</li>
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<li>执行以下命令启动测试页面运行时：</li>
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</ol>
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<pre>python start_test_runtime.py</pre>
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<p>然后在浏览器中访问：<strong>http://localhost:8006/test_page.html</strong></p>
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<pre>python start.py</pre>
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<p>然后在浏览器中访问：<strong>http://localhost:8006/index.html</strong></p>
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`;
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document.body.appendChild(warningDiv);
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});
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Before Width: | Height: | Size: 2.4 MiB After Width: | Height: | Size: 2.4 MiB |
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Before Width: | Height: | Size: 6.6 MiB After Width: | Height: | Size: 6.6 MiB |
@@ -25,7 +25,7 @@ class TestRuntimeHttpServer:
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@property
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def page_url(self) -> str:
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return f"http://127.0.0.1:{self.port}/test_page.html"
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return f"http://127.0.0.1:{self.port}/index.html"
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@property
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def bridge_url(self) -> str:
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