🧠 唤醒词训练知识图谱

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graph TB
    subgraph 前端层["前端 Dashboard"]
        UI[Web 管理界面]
    end

    subgraph API层["jabobo-backend REST API (FastAPI, port 8007)"]
        TrainAPI["POST /api/user/wake-word/train
trigger_wake_word_training()"]
        StatusAPI["GET /api/user/wake-word/train/status
get_wake_word_status()"]
        SyncAPI["POST /api/user/sync-config
sync_config()"]
        GetConfig["GET /api/user/config
get_user_config()"]
    end

    subgraph 核心业务层["核心业务流程"]
        direction TB
        NORMALIZE["_normalize_wake_word()
标准化唤醒词名"]
        DISPLAY["_wake_word_to_display()
生成显示名"]
        TRAIN["_run_wakeword_training()
异步训练任务"]
        UPDATE_STATUS["_update_wake_word_status()
更新数据库状态"]
    end

    subgraph 外部系统["外部系统"]
        CMD1["train_wakeword.py
--generate-samples
（TTS 生成 500 条样本）"]
        CMD2["train_wakeword.py
（特征提取+训练）"]
        CMD3["deploy_wakeword.py
（OTA 部署 .tflite）"]
    end

    subgraph 数据层["MySQL 数据库"]
        DB[("user_personas 表")]
    end

    subgraph 固件层["ESP32 设备"]
        DEVICE["捷宝宝硬件"]
        OTA_RECEIVER["OTA 接收+模型加载"]
    end

    UI -->|"POST /user/wake-word/train"| TrainAPI
    UI -->|"GET /user/wake-word/train/status"| StatusAPI
    UI -->|"POST /user/sync-config"| SyncAPI
    UI -->|"GET /user/config"| GetConfig

    TrainAPI -->|"asyncio.create_task"| TRAIN
    SyncAPI -->|"if wake_word_text changed"| TRAIN
    GetConfig -.->|"read model_status"| DB
    StatusAPI -->|"查询状态"| DB

    TRAIN --> NORMALIZE
    NORMALIZE --> DISPLAY
    TRAIN --> UPDATE_STATUS

    TRAIN -->|"检查已有模型"| CMD2
    TRAIN -->|"生成样本"| CMD1
    CMD1 --> CMD2
    CMD2 --> CMD3
    CMD3 -->|"OTA 推送"| OTA_RECEIVER
    OTA_RECEIVER --> DEVICE

    UPDATE_STATUS -->|"UPDATE model_status"| DB

    style 前端层 fill:#0f766e,stroke:#14b8a6,color:#fff
    style API层 fill:#1d4ed8,stroke:#3b82f6,color:#fff
    style 核心业务层 fill:#15803d,stroke:#22c55e,color:#fff
    style 外部系统 fill:#b45309,stroke:#f59e0b,color:#fff
    style 数据层 fill:#7c3aed,stroke:#a855f7,color:#fff
    style 固件层 fill:#b91c1c,stroke:#ef4444,color:#fff

%%{init: {'theme': 'dark', 'themeVariables': { 'primaryColor': '#1e293b', 'primaryTextColor': '#f1f5f9', 'primaryBorderColor': '#475569', 'lineColor': '#38bdf8', 'secondaryColor': '#334155', 'tertiaryColor': '#0f172a'}}}%%
graph LR
    subgraph API入口["API 入口"]
        T["trigger_wake_word_training()
POST /user/wake-word/train"]
        S["sync_config()
POST /user/sync-config"]
        ST["get_wake_word_status()
GET /user/wake-word/train/status"]
        GC["get_user_config()
GET /user/config"]
    end

    subgraph 辅助函数["辅助函数"]
        NW["_normalize_wake_word()"]
        WD["_wake_word_to_display()"]
        UV["verify_user()
用户认证"]
        GVC["get_valid_cursor()
数据库游标"]
    end

    subgraph 核心训练["核心训练"]
        RT["_run_wakeword_training()"]
        US["_update_wake_word_status()"]
    end

    subgraph 数据库["MySQL"]
        CONN["db.connect()"]
        QUERY["SELECT / UPDATE
user_personas"]
    end

    subgraph 外部进程["外部进程"]
        CMD1["train_wakeword.py
--generate-samples"]
        CMD2["train_wakeword.py
训练"]
        CMD3["deploy_wakeword.py
OTA"]
    end

    T -->|"asyncio.create_task"| RT
    S -.->|"if wake_word_text"| NW
    NW --> RT
    ST --> UV --> CONN --> QUERY
    GC --> UV
    GC --> GVC --> CONN

    RT --> WD
    RT --> CMD1 --> CMD2 --> CMD3
    RT --> US --> CONN -->|"UPDATE model_status"| QUERY

    style API入口 fill:#1e3a5f,stroke:#38bdf8,color:#fff
    style 辅助函数 fill:#1e3a5f,stroke:#38bdf8,color:#fff
    style 核心训练 fill:#1e3a5f,stroke:#22c55e,color:#fff
    style 数据库 fill:#4a1a7a,stroke:#a855f7,color:#fff
    style 外部进程 fill:#5c3d0a,stroke:#f59e0b,color:#fff

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sequenceDiagram
    participant U as 用户/前端
    participant API as jabobo-backend
    participant MEM as 进程缓存
_wake_word_tasks
    participant DB as MySQL
    participant CONDA as Conda wakeword
TTS + 训练脚本
    participant DEV as ESP32 设备

    U->>API: POST /user/wake-word/train
{device_id, wake_word: "Hey Jabra"}
    Note over API: 标准化: hey_jabra
显示名: Hey Jabra
    API->>MEM: {status: "running"}
    API-->>U: 200 任务已启动
    API-->>API: asyncio.create_task()

    rect rgb(30, 58, 95)
        Note over API,CONDA: 阶段1: TTS 生成 500 条样本
        alt 已有 .tflite
            API-->>API: 跳过训练，直接部署
        else 首次训练
            API->>CONDA: train_wakeword.py --generate-samples
--text "Hey Jabra" --max-samples 500
--voices lessac,amy,joe --length-scales 0.5~1.0
            Note over CONDA: 多种音色 × 5 种语速
= 数千条 WAV 样本
            CONDA-->>API: 样本生成完成
        end
    end

    rect rgb(21, 128, 61)
        Note over API,CONDA: 阶段2: 模型训练
        API->>CONDA: train_wakeword.py
        Note over CONDA: MFCC 特征提取 → CNN 训练 → TFLite 量化导出
        CONDA-->>API: trained_models/hey_jabra/hey_jabra.tflite
    end

    rect rgb(180, 83, 9)
        Note over API,DEV: 阶段3: OTA 部署
        API->>CONDA: deploy_wakeword.py
        CONDA-->>DEV: OTA 推送 .tflite 模型
        DEV-->>CONDA: 部署确认
    end

    rect rgb(124, 58, 237)
        Note over API,DB: 阶段4: 数据库持久化
        API->>DB: UPDATE user_personas SET wake_word_model_status=1
        API->>MEM: {status: "done", elapsed: 187s}
    end

    U->>API: GET /user/wake-word/train/status
    API->>MEM: 读取状态
    API-->>U: {status: "done", elapsed_seconds: 187}

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stateDiagram-v2
    [*] --> 未训练 : 设备绑定
status = 0
    未训练 --> 训练中 : POST /user/wake-word/train
    训练中 --> 已部署 : 训练+部署成功
status = 1
    训练中 --> 训练失败 : 异常退出
status = 2
    已部署 --> 训练中 : 重新训练
    训练失败 --> 训练中 : 重试

%%{init: {'theme': 'dark', 'themeVariables': { 'primaryColor': '#1e293b', 'primaryTextColor': '#f1f5f9', 'primaryBorderColor': '#475569', 'lineColor': '#38bdf8', 'secondaryColor': '#334155', 'tertiaryColor': '#0f172a'}}}%%
erDiagram
    user_login ||--o{ user_personas : has

    user_login {
        int id PK
        string username UK
    }

    user_personas {
        int id PK
        string username FK
        string jabobo_id UK
        json personas
        text memory
        string websocket_url
        string asr_provider
        string tts_provider
        string llm_provider
        boolean rag_enabled
        string wake_word_text "用户设定的唤醒词"
        int wake_word_model_status "0=未训练 1=已部署 2=失败"
        string current_version
        string expected_version
        json voiceprint_list
    }