feat: 支持配置 Whisper 模型并优化 API Key 管理

- 添加 download_model.sh 脚本，支持从 Hugging Face 下载 Whisper 语音识别模型
- 在 bot 状态和序列化接口中新增 api_key 字段，支持持久化存储
- 更新前端 i18n 文本，将“新的 API Key”改为“API Key”，明确其为必填项
- 设置 axios 默认携带凭证，确保身份验证
- 将管理面板名称从“Nanobot”更新为“Unisbot”

backend/services/bot_service.py

@@ -424,6 +424,7 @@ def serialize_bot_detail(bot: BotInstance) -> Dict[str, Any]:
         "image_tag": bot.image_tag,
         "llm_provider": runtime["llm_provider"],
         "llm_model": runtime["llm_model"],
+        "api_key": runtime["api_key"],
         "api_base": runtime["api_base"],
         "temperature": runtime["temperature"],
         "top_p": runtime["top_p"],

download_model.sh

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

frontend/src/i18n/app.zh-cn.ts

@@ -1,5 +1,5 @@
 export const appZhCn = {
-  title: 'Nanobot 管理面板',
+  title: 'Unisbot 管理面板',
   theme: '主题',
   language: '语言',
   dark: '深色',

frontend/src/i18n/dashboard.en.ts

@@ -69,7 +69,7 @@ export const dashboardEn = {
   feedbackSaveFail: 'Failed to save feedback.',
   feedbackMessagePending: 'Message is not synced yet. Please retry in a moment.',
   sendFailMsg: (msg: string) => `Command delivery failed: ${msg}`,
-  providerRequired: 'Set provider/model/new API key before testing.',
+  providerRequired: 'Set provider/model/API key before testing.',
   connOk: (preview: string) => (preview ? `Connection passed, models: ${preview}` : 'Connection passed'),
   connFail: (msg: string) => `Failed: ${msg}`,
   configUpdated: 'Configuration updated (effective after bot restart).',
@@ -265,8 +265,8 @@ export const dashboardEn = {
   baseImageReadonly: 'Base Image',
   modelName: 'Model Name',
   modelNamePlaceholder: 'e.g. qwen-plus',
-  newApiKey: 'New API Key (optional)',
+  newApiKey: 'API Key',
-  newApiKeyPlaceholder: 'Only updated when filled',
+  newApiKeyPlaceholder: 'Enter API key',
   testing: 'Testing...',
   testModelConnection: 'Test model connection',
   cancel: 'Cancel',

frontend/src/i18n/dashboard.zh-cn.ts

@@ -69,7 +69,7 @@ export const dashboardZhCn = {
   feedbackSaveFail: '反馈保存失败。',
   feedbackMessagePending: '消息尚未同步，暂不可反馈。',
   sendFailMsg: (msg: string) => `指令发送失败：${msg}`,
-  providerRequired: '请填写 Provider、模型和新 API Key 后再测试。',
+  providerRequired: '请填写 Provider、模型和 API Key 后再测试。',
   connOk: (preview: string) => (preview ? `连接成功，模型: ${preview}` : '连接成功'),
   connFail: (msg: string) => `连接失败: ${msg}`,
   configUpdated: '配置已更新（重启 Bot 后生效）。',
@@ -265,8 +265,8 @@ export const dashboardZhCn = {
   baseImageReadonly: '基础镜像',
   modelName: '模型名称',
   modelNamePlaceholder: '如 qwen-plus',
-  newApiKey: '新的 API Key（留空不更新）',
+  newApiKey: 'API Key',
-  newApiKeyPlaceholder: '输入新 Key 才会更新',
+  newApiKeyPlaceholder: '输入 API Key',
   testing: '测试中...',
   testModelConnection: '测试模型连接',
   cancel: '取消',

frontend/src/main.tsx

@@ -1,11 +1,14 @@
 import { StrictMode } from 'react'
 import { createRoot } from 'react-dom/client'
+import axios from 'axios'
 import './index.css'
 import App from './App.tsx'
 import { LucentPromptProvider } from './components/lucent/LucentPromptProvider.tsx'
 import { setupBotAccessAuth } from './utils/botAccess.ts'
 import { setupPanelAccessAuth } from './utils/panelAccess.ts'
 
+axios.defaults.withCredentials = true
+
 setupPanelAccessAuth();
 setupBotAccessAuth();
 

frontend/src/modules/dashboard/hooks/useDashboardBotEditor.ts

@@ -97,7 +97,7 @@ export function useDashboardBotEditor({
       llm_provider: provider,
       llm_model: bot.llm_model || '',
       image_tag: bot.image_tag || '',
-      api_key: '',
+      api_key: bot.api_key || '',
       api_base: bot.api_base || '',
       temperature: clampTemperature(bot.temperature ?? 0.2),
       top_p: bot.top_p ?? 1,

frontend/src/types/bot.ts

@@ -28,6 +28,7 @@ export interface BotState {
   image_tag?: string;
   llm_provider?: string;
   llm_model?: string;
+  api_key?: string;
   api_base?: string;
   temperature?: number;
   top_p?: number;