75 lines
2.3 KiB
Bash
Executable File
75 lines
2.3 KiB
Bash
Executable File
#!/usr/bin/env bash
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# ==========================================
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# Whisper ggml 模型下载脚本
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# 下载的模型将存放在 data/model 目录下
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# ==========================================
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# 确保在项目根目录运行
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SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
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TARGET_DIR="${SCRIPT_DIR}/data/model"
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# 创建目标目录
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mkdir -p "$TARGET_DIR"
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# Hugging Face 的 whisper.cpp 模型仓库地址
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# 使用 hf-mirror 镜像加速国内下载
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BASE_URL="https://hf-mirror.com/ggerganov/whisper.cpp/resolve/main"
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echo "=========================================="
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echo "请选择要下载的 Whisper 语音识别模型："
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echo "1) tiny (最小，速度最快，约 40MB)"
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echo "2) base (基础，速度快，约 74MB)"
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echo "3) small (当前默认，平衡，约 240MB)"
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echo "4) medium (推荐，效果更好，约 770MB)"
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echo "5) large-v3 (最大，效果最好，约 1.5GB)"
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echo "=========================================="
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read -p "请输入对应的数字 [1-5，默认 4]: " choice
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MODEL_NAME=""
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case $choice in
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1) MODEL_NAME="ggml-tiny-q8_0.bin" ;;
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2) MODEL_NAME="ggml-base-q8_0.bin" ;;
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3) MODEL_NAME="ggml-small-q8_0.bin" ;;
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4|"") MODEL_NAME="ggml-medium-q8_0.bin" ;;
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5) MODEL_NAME="ggml-large-v3-q8_0.bin" ;;
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*)
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echo "无效的选择，使用默认选项 4 (medium)"
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MODEL_NAME="ggml-medium-q8_0.bin"
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;;
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esac
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echo ""
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echo "准备下载模型: $MODEL_NAME"
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echo "保存路径: $TARGET_DIR/$MODEL_NAME"
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echo ""
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# 下载文件
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DOWNLOAD_URL="${BASE_URL}/${MODEL_NAME}"
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if command -v wget >/dev/null 2>&1; then
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echo "使用 wget 下载中..."
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wget -c --show-progress "$DOWNLOAD_URL" -O "$TARGET_DIR/$MODEL_NAME"
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elif command -v curl >/dev/null 2>&1; then
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echo "使用 curl 下载中..."
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curl -L -C - -o "$TARGET_DIR/$MODEL_NAME" "$DOWNLOAD_URL"
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else
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echo "错误：找不到 wget 或 curl 命令，无法下载文件。"
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exit 1
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fi
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if [ $? -eq 0 ]; then
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echo ""
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echo "✅ 下载成功！"
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echo "模型文件已保存到: $TARGET_DIR/$MODEL_NAME"
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echo ""
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echo "请记得更新 .env.prod 或 backend/.env 文件中的配置："
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echo "STT_MODEL=$MODEL_NAME"
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echo "修改后重启后端容器即可生效。"
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else
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echo ""
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echo "❌ 下载失败，请检查网络连接或稍后重试。"
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exit 1
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fi
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