flat: 暂存
This commit is contained in:
Apcallover
@@ -3,6 +3,7 @@ import { electronApp, optimizer, is } from "@electron-toolkit/utils";
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import icon from "../../resources/icon.png?asset";
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import { setupLiveHandlers } from "./ipc/live";
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import { setupPromptHandlers } from "./ipc/prompt";
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import { setupWorkflowHandlers } from "./ipc/workflow";
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import { preload, indexHtml, ELECTRON_RENDERER_URL } from "./config";
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// 在开发环境下启用热重载
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@@ -75,6 +76,8 @@ app.whenReady().then(() => {
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setupPromptHandlers();
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setupWorkflowHandlers();
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createWindow();
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app.on("activate", function () {
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@@ -1,14 +1,8 @@
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import { ipcMain, BrowserWindow } from "electron";
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import { preload, indexHtml, ELECTRON_RENDERER_URL } from "../config";
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import { showPrompt } from "../utils/tools";
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import { OllamaClient } from "../utils/ollama-client";
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let liveWindow: BrowserWindow | null = null;
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const client = new OllamaClient({
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baseUrl: "http://127.0.0.1:11434", // 可选，默认值
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timeout: 30000, // 可选，默认30秒
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});
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// 直播相关的主进程处理
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export function setupLiveHandlers() {
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let LiveSessionId = null;
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@@ -104,7 +98,7 @@ export function setupLiveHandlers() {
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contextIsolation: false,
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},
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});
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// liveWindow.webContents.openDevTools();
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liveWindow.webContents.openDevTools();
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liveWindow.on("closed", () => {
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liveWindow = null;
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});
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@@ -128,24 +122,6 @@ export function setupLiveHandlers() {
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return { success: false, error: error.message };
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}
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});
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ipcMain.handle("ollama-test", async (_, jobInfo) => {
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try {
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const result = await client.generateText({
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model: "qwen:7b",
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prompt: `请根据提供的 json 数据：${jobInfo}，直接生成一段用于吸引求职者投递的岗位介绍文案。文案需：
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1、简洁、有力，突出岗位核心价值和吸引力。
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2、不包含任何多余的开头、结尾、解释或废话。
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3、目标是立即抓住用户眼球并促使他们投递简历。
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4、不含任何废话或与岗位无关的内容
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**要求：**只输出生成的岗位介绍文案本身。`,
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});
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return { success: true, data: result };
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} catch (error: any) {
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console.error("Ollama error:", error);
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return { success: false, error: error.message };
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}
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});
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}
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async function getSessionId(requestBody: object) {
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@@ -2,7 +2,7 @@ import { ipcMain, dialog } from "electron";
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export function setupPromptHandlers() {
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// 提示信息处理
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ipcMain.handle("show-prompt", async (event) => {
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ipcMain.handle("show-prompt", async () => {
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dialog.showMessageBox({
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type: "info",
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title: "提示",
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329
src/main/ipc/workflow.ts
Normal file
329
src/main/ipc/workflow.ts
Normal file
@@ -0,0 +1,329 @@
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import { ipcMain, BrowserWindow } from "electron";
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import { spawn } from "child_process";
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import { showPrompt } from "../utils/tools";
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import { preload, indexHtml, ELECTRON_RENDERER_URL } from "../config";
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import os from "os";
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import http from "http";
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let InstallWindows: BrowserWindow | null = null;
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export function setupWorkflowHandlers() {
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let lastJobSummary = "这是我们今天介绍的第一个岗位";
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// 打开安装窗口
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ipcMain.handle("open-install-window", async (_, args) => {
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try {
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if (InstallWindows) {
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InstallWindows.focus();
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showPrompt("下载已打开", "info");
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return { success: true };
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}
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const { width, height, path } = args;
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let installUrl = `${ELECTRON_RENDERER_URL}/#/${path}`;
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console.log(installUrl);
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InstallWindows = new BrowserWindow({
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title: "模型下载",
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width,
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height,
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minimizable: false, // 是否可以最小化
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maximizable: false, // 是否可以最小化
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closable: true, // 窗口是否可关闭
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alwaysOnTop: false, // 窗口是否永远在别的窗口的上面
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webPreferences: {
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preload,
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nodeIntegration: true,
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contextIsolation: false,
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},
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});
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// InstallWindows.webContents.openDevTools();
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InstallWindows.on("closed", () => {
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InstallWindows = null;
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});
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if (ELECTRON_RENDERER_URL) {
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InstallWindows.loadURL(installUrl);
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} else {
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InstallWindows.loadFile(indexHtml, { hash: `/${path}` });
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}
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return { success: true };
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} catch (error: any) {
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return { success: false, error: error.message };
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}
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});
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// 监听来自渲染器进程的 'install-ollama' 事件
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ipcMain.handle("install-ollama-and-model", async (event) => {
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const webContents = event.sender; // 获取发送事件的窗口
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const platform = os.platform();
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const modelToPull = "qwen3:8b";
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const sendStatus = (status) => {
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if (webContents && !webContents.isDestroyed()) {
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webContents.send("install-progress", { status });
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}
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};
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try {
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sendStatus("Checking Ollama installation...");
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try {
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await streamCommand(
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"ollama",
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["-v"],
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webContents,
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"install-progress",
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);
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sendStatus("Ollama is already installed.");
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} catch (error) {
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// Ollama 未安装，执行安装
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sendStatus("Ollama not found. Starting installation...");
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if (platform === "darwin" || platform === "linux") {
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// macOS / Linux - 使用官方的 curl 脚本
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const installCommand =
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"curl -fsSL https://ollama.com/install.sh | sh";
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await streamCommand(
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"sh",
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["-c", installCommand],
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webContents,
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"install-progress",
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);
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} else if (platform === "win32") {
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// Windows - 使用 PowerShell 下载并静默安装
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const psScript = `
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$ProgressPreference = 'SilentlyContinue';
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$tempPath = [System.IO.Path]::Combine($env:TEMP, 'OllamaSetup.exe');
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Write-Host 'Downloading OllamaSetup.exe...';
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Invoke-WebRequest -Uri 'https://ollama.com/download/OllamaSetup.exe' -OutFile $tempPath;
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Write-Host 'Download complete. Starting silent installer...';
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Start-Process -FilePath $tempPath -ArgumentList '/S' -Wait;
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Write-Host 'Installation complete. Cleaning up...';
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Remove-Item $tempPath;
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Write-Host 'Done.';
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`;
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await streamCommand(
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"powershell",
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[
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"-ExecutionPolicy",
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"Bypass",
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"-NoProfile",
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"-Command",
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psScript,
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],
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webContents,
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"install-progress",
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);
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} else {
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throw new Error(`Unsupported platform: ${platform}`);
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}
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sendStatus("Ollama installation complete.");
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}
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// --- 步骤 2: 拉取模型 ---
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sendStatus(
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`Pulling model: ${modelToPull}... (This may take a while)`,
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);
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await streamCommand(
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"ollama",
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["pull", modelToPull],
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webContents,
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"install-progress",
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);
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sendStatus(`Model ${modelToPull} pull complete.`);
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return {
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success: true,
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message: "Installation and model pull successful.",
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};
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} catch (error: any) {
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console.error(error);
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sendStatus(`Error: ${error.message}`);
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return { success: false, message: error.message };
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}
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});
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// 将整个工作流封装在 IPC Handler 中
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ipcMain.handle("run-job-workflow", async (_, userQuery) => {
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let currentJobData = userQuery || {};
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let answerText = "";
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try {
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console.log("工作流: 正在调用 Ollama 生成脚本...");
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const systemPromptTemplate = `# 角色 (Role) \n你是一个顶级的招聘KOL和直播带岗专家。你的风格是：专业、中立、风趣，能一针见血地分析岗位优劣。你不是一个AI助手，你就是这个角色。 \n\n# 上下文 (Context) \n我正在运行一个自动化工作流。我会\"一个一个\"地喂给你岗位数据。\n\n # 任务 (Task) \n你的任务是执行以下两个操作，并严格按照“输出格式”返回内容：\n1. 生成口播稿：根据【输入数据A】(上一个岗位的摘要) 和【输入数据B】(当前岗位的JSON)，生成一段完整的、约90秒的口播稿。\n2. 生成新摘要：为【输入数据B】的“当前岗位”生成一个简短的摘要（例如：XX公司的XX岗），以便在下一次调用时使用。\n\n# 核心指令 (Core Instruction)\n### 口播稿的生成规则 (Rules for the Script) \n1. 衔接：口播稿必须以一个自然的“过渡句”开头（基于【输入数据A】）。 特殊情况：如果【输入数据A】是“这是我们今天介绍的第一个岗位。”，则开头应是“热场”或“总起”，而不是衔接。 \n2. 内容：必须介绍岗位名称 \`jobTitle\`。 \n3. 提炼：从 \`jobLocation\`, \`companyName\`, \`education\`,\`experience\`，\`scale\` 中提炼“亮点 (Pro)”。 \n4. 翻译：用“人话”翻译 \`description\`。 \n5. 视角：你是在“评测”这个岗位，而不是在“推销”。\n\n### 口播稿的纯文本要求 (Pure Text Rules for the Script ONLY) \n**[重要]** 以下规则 *仅适用于* “口播稿”部分，不适用于“新摘要”部分： \n1. 绝不包含任何Markdown格式 (\`**\`, \`#\`)。 \n2. 绝不包含任何标签、括号或元数据 (\`[]\`, \`()\`)。 \n3. 绝不包含任何寒暄、问候、或自我介绍 (例如 \"你好\", \"当然\")。 \n4. 必须是可以直接朗读的、完整的、流畅的纯文本。\n\n# 输入数据 (Input Data)\n\n## 输入数据A (上一个岗位摘要) \n${lastJobSummary}\n\n## 输入数据B (当前岗位JSON)\n\`\`\`json\n${JSON.stringify(currentJobData, null, 2)}\n\`\`\`\n\n# 输出格式 (Output Format)\n**[绝对严格的指令]** \n你必须严格按照下面这个“两部分”格式输出，使用 \`---NEXT_SUMMARY---\` 作为唯一的分隔符。 绝不在分隔符之外添加任何多余的文字、解释或Markdown。 \n\n[这里是AI生成的、符合上述所有“纯文本要求”的完整口播稿] \n---NEXT_SUMMARY--- \n[这里是AI为“当前岗位”生成的简短新摘要]`;
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answerText = await runOllamaNonStream(
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systemPromptTemplate,
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"qwen3:8b",
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);
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if (!answerText) {
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throw new Error("Ollama 返回为空");
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}
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} catch (e) {
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return "抱歉，AI 模型在生成脚本时出错。";
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}
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try {
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console.log("工作流: 正在解析 AI 输出...");
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let script = "抱歉，AI没有按预定格式返回脚本，请稍后重试。";
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let summary = "这是我们今天介绍的第一个岗位。"; // 这是一个安全的“重置”摘要
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if (answerText && typeof answerText === "string") {
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const parts = answerText.split("---NEXT_SUMMARY---");
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if (parts[0] && parts[0].trim() !== "") {
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script = parts[0].trim();
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}
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if (parts[1] && parts[1].trim() !== "") {
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summary = parts[1].trim();
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}
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}
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console.log("工作流: 正在更新状态...");
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lastJobSummary = summary; // 关键：更新主进程中的状态
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console.log("工作流: 完成，返回口播稿。");
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return { success: true, data: script }; // 将最终的“口播稿”返回给渲染进程
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} catch (e: any) {
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console.error("代码运行或变量更新节点出错:", e);
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return "抱歉，处理 AI 响应时出错。";
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}
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});
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// 检查 Ollama 服务器是否正在运行
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ipcMain.handle("check-ollama-status", async () => {
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return await checkOllamaServer();
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});
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// 处理器：检查服务，如果没运行，就用一个轻量命令唤醒它
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ipcMain.handle("ensure-ollama-running", async () => {
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let isRunning = await checkOllamaServer();
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if (isRunning) {
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return {
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success: true,
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message: "Ollama服务器已在运行.",
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};
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}
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// 服务未运行。
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// 我们运行 'ollama ps'。这个命令会与服务通信，
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// 如果服务没启动，Ollama CLI 会自动启动它。
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try {
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await runCommand("ollama", ["ps"]);
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// 给服务一点启动时间 (例如 2 秒)
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await new Promise((resolve) => setTimeout(resolve, 2000));
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// 再次检查
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isRunning = await checkOllamaServer();
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if (isRunning) {
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return {
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success: true,
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message: "Ollama 已在后台启动",
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};
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} else {
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return {
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success: false,
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message: "服务启动失败",
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};
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}
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} catch (error: any) {
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console.error("错误:", error);
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return {
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success: false,
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||||
message: `错误: ${error.message}`,
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||||
};
|
||||
}
|
||||
});
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||||
}
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||||
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||||
// 辅助函数：检查 Ollama API 是否可访问
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||||
function checkOllamaServer() {
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return new Promise((resolve) => {
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// 默认端口是 11434
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const req = http.get("http://127.0.0.1:11434/", (res) => {
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||||
// "Ollama is running" 的响应码是 200
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resolve(res.statusCode === 200);
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});
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||||
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||||
// 如果连接被拒绝 (ECONNREFUSED)，则服务未运行
|
||||
req.on("error", () => {
|
||||
resolve(false);
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||||
});
|
||||
});
|
||||
}
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||||
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||||
// 辅助函数：运行一个简单的命令并等待它完成
|
||||
function runCommand(command, args) {
|
||||
return new Promise((resolve, reject) => {
|
||||
const process = spawn(command, args, { shell: true });
|
||||
process.on("close", (code) => {
|
||||
if (code === 0) {
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||||
resolve(null);
|
||||
} else {
|
||||
reject(new Error(`Command failed with code ${code}`));
|
||||
}
|
||||
});
|
||||
process.on("error", (err) => reject(err));
|
||||
});
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||||
}
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||||
// 这是一个非流式的 Ollama 助手函数
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||||
async function runOllamaNonStream(prompt, model = "qwen3:8b") {
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||||
try {
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||||
const response = await fetch("http://127.0.0.1:11434/api/chat", {
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||||
method: "POST",
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||||
headers: { "Content-Type": "application/json" },
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||||
body: JSON.stringify({
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||||
model: model,
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||||
messages: [{ role: "user", content: prompt }],
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stream: false, // 关键：关闭流式
|
||||
}),
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||||
});
|
||||
|
||||
if (!response.ok) {
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||||
throw new Error(`Ollama API error: ${response.statusText}`);
|
||||
}
|
||||
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||||
const data = await response.json();
|
||||
|
||||
// data.message.content 包含了完整的 AI 回复
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||||
return data.message.content;
|
||||
} catch (error) {
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||||
console.error("Ollama Chat Error:", error);
|
||||
return null; // 返回 null 以便后续逻辑处理
|
||||
}
|
||||
}
|
||||
|
||||
function streamCommand(command, args, webContents, eventName) {
|
||||
return new Promise((resolve, reject) => {
|
||||
const process = spawn(command, args, { shell: true });
|
||||
|
||||
const send = (channel, data) => {
|
||||
if (webContents && !webContents.isDestroyed()) {
|
||||
webContents.send(channel, data);
|
||||
}
|
||||
};
|
||||
|
||||
process.stdout.on("data", (data) => {
|
||||
send(eventName, { type: "stdout", data: data.toString() });
|
||||
});
|
||||
|
||||
process.stderr.on("data", (data) => {
|
||||
send(eventName, { type: "stderr", data: data.toString() });
|
||||
});
|
||||
|
||||
process.on("close", (code) => {
|
||||
if (code === 0) {
|
||||
resolve(null);
|
||||
} else {
|
||||
reject(new Error(`Process exited with code ${code}`));
|
||||
}
|
||||
});
|
||||
|
||||
process.on("error", (err) => {
|
||||
reject(err);
|
||||
});
|
||||
});
|
||||
}
|
||||
@@ -1,271 +0,0 @@
|
||||
import { type ClientRequest, type IncomingMessage } from "http";
|
||||
import * as http from "http";
|
||||
|
||||
interface OllamaOptions {
|
||||
baseUrl?: string;
|
||||
timeout?: number;
|
||||
}
|
||||
|
||||
interface GenerateParams {
|
||||
model: string;
|
||||
prompt: string;
|
||||
system?: string;
|
||||
template?: string;
|
||||
context?: number[];
|
||||
stream?: boolean;
|
||||
format?: "json";
|
||||
options?: {
|
||||
temperature?: number;
|
||||
top_p?: number;
|
||||
top_k?: number;
|
||||
seed?: number;
|
||||
num_predict?: number;
|
||||
stop?: string[];
|
||||
num_ctx?: number;
|
||||
};
|
||||
}
|
||||
|
||||
interface GenerateResponse {
|
||||
model: string;
|
||||
created_at: string;
|
||||
response: string;
|
||||
context: number[];
|
||||
done: boolean;
|
||||
total_duration: number;
|
||||
load_duration: number;
|
||||
prompt_eval_duration: number;
|
||||
eval_duration: number;
|
||||
prompt_eval_count: number;
|
||||
eval_count: number;
|
||||
}
|
||||
|
||||
interface ModelInfo {
|
||||
name: string;
|
||||
size: number;
|
||||
digest: string;
|
||||
details: {
|
||||
format: string;
|
||||
family: string;
|
||||
families: string[];
|
||||
parameter_size: string;
|
||||
quantization_level: string;
|
||||
};
|
||||
}
|
||||
|
||||
interface ListModelsResponse {
|
||||
models: ModelInfo[];
|
||||
}
|
||||
|
||||
export class OllamaClient {
|
||||
private readonly baseUrl: string;
|
||||
private readonly timeout: number;
|
||||
|
||||
constructor(options: OllamaOptions = {}) {
|
||||
this.baseUrl = options.baseUrl || "http://localhost:11434";
|
||||
this.timeout = options.timeout || 30000;
|
||||
}
|
||||
|
||||
private async request<T>(
|
||||
path: string,
|
||||
method = "GET",
|
||||
body?: unknown,
|
||||
): Promise<T> {
|
||||
return new Promise((resolve, reject) => {
|
||||
const url = new URL(path, this.baseUrl);
|
||||
const options = {
|
||||
method,
|
||||
hostname: url.hostname,
|
||||
port: url.port || "11434",
|
||||
path: url.pathname,
|
||||
headers: {
|
||||
"Content-Type": "application/json",
|
||||
},
|
||||
timeout: this.timeout,
|
||||
};
|
||||
|
||||
const req: ClientRequest = http.request(
|
||||
options,
|
||||
(res: IncomingMessage) => {
|
||||
let data = "";
|
||||
|
||||
res.on("data", (chunk) => {
|
||||
data += chunk;
|
||||
});
|
||||
|
||||
res.on("end", () => {
|
||||
if (
|
||||
res.statusCode &&
|
||||
res.statusCode >= 200 &&
|
||||
res.statusCode < 300
|
||||
) {
|
||||
try {
|
||||
resolve(JSON.parse(data));
|
||||
} catch (e) {
|
||||
reject(
|
||||
new Error("Failed to parse response data"),
|
||||
);
|
||||
}
|
||||
} else {
|
||||
reject(
|
||||
new Error(
|
||||
`HTTP Error: ${res.statusCode} ${res.statusMessage}`,
|
||||
),
|
||||
);
|
||||
}
|
||||
});
|
||||
},
|
||||
);
|
||||
|
||||
req.on("error", reject);
|
||||
|
||||
req.on("timeout", () => {
|
||||
req.destroy();
|
||||
reject(new Error("Request timeout"));
|
||||
});
|
||||
|
||||
if (body) {
|
||||
req.write(JSON.stringify(body));
|
||||
}
|
||||
req.end();
|
||||
});
|
||||
}
|
||||
|
||||
async generate(params: GenerateParams): Promise<GenerateResponse> {
|
||||
const result = await this.request<GenerateResponse>(
|
||||
"/api/generate",
|
||||
"POST",
|
||||
{
|
||||
...params,
|
||||
stream: false,
|
||||
},
|
||||
);
|
||||
|
||||
// 如果响应是JSON格式，尝试解析
|
||||
if (params.format === "json" && result.response) {
|
||||
try {
|
||||
const parsed = JSON.parse(result.response);
|
||||
result.response =
|
||||
parsed.content || parsed.text || result.response;
|
||||
} catch (e) {
|
||||
console.warn(
|
||||
"Failed to parse JSON response, returning raw response",
|
||||
);
|
||||
}
|
||||
}
|
||||
|
||||
return result;
|
||||
}
|
||||
|
||||
/**
|
||||
* 生成文本响应，直接返回文本内容
|
||||
*/
|
||||
async generateText(
|
||||
params: Omit<GenerateParams, "format">,
|
||||
): Promise<string> {
|
||||
const result = await this.generate({
|
||||
...params,
|
||||
format: undefined, // 确保不使用 JSON 格式
|
||||
});
|
||||
return result.response;
|
||||
}
|
||||
|
||||
async streamGenerate(
|
||||
params: GenerateParams,
|
||||
onResponse: (response: GenerateResponse) => void,
|
||||
onError?: (error: Error) => void,
|
||||
): Promise<void> {
|
||||
const url = new URL("/api/generate", this.baseUrl);
|
||||
const options = {
|
||||
method: "POST",
|
||||
hostname: url.hostname,
|
||||
port: url.port || "11434",
|
||||
path: url.pathname,
|
||||
headers: {
|
||||
"Content-Type": "application/json",
|
||||
},
|
||||
};
|
||||
|
||||
return new Promise<void>((resolve, reject) => {
|
||||
const req = http.request(options, (res) => {
|
||||
let buffer = "";
|
||||
|
||||
res.on("data", (chunk) => {
|
||||
buffer += chunk;
|
||||
const lines = buffer.split("\n");
|
||||
buffer = lines.pop() || "";
|
||||
|
||||
for (const line of lines) {
|
||||
if (line.trim()) {
|
||||
try {
|
||||
const response = JSON.parse(
|
||||
line,
|
||||
) as GenerateResponse;
|
||||
onResponse(response);
|
||||
} catch (e) {
|
||||
const error = new Error(
|
||||
"Failed to parse streaming response",
|
||||
);
|
||||
onError?.(error);
|
||||
console.error(error, e);
|
||||
}
|
||||
}
|
||||
}
|
||||
});
|
||||
|
||||
res.on("end", () => {
|
||||
if (buffer.trim()) {
|
||||
try {
|
||||
const response = JSON.parse(
|
||||
buffer,
|
||||
) as GenerateResponse;
|
||||
onResponse(response);
|
||||
} catch (e) {
|
||||
const error = new Error(
|
||||
"Failed to parse final streaming response",
|
||||
);
|
||||
onError?.(error);
|
||||
console.error(error, e);
|
||||
}
|
||||
}
|
||||
resolve();
|
||||
});
|
||||
});
|
||||
|
||||
req.on("error", (error) => {
|
||||
onError?.(error);
|
||||
reject(error);
|
||||
});
|
||||
|
||||
req.write(JSON.stringify({ ...params, stream: true }));
|
||||
req.end();
|
||||
});
|
||||
}
|
||||
|
||||
async listModels(): Promise<ListModelsResponse> {
|
||||
return this.request<ListModelsResponse>("/api/tags");
|
||||
}
|
||||
|
||||
async pullModel(modelName: string): Promise<void> {
|
||||
await this.request("/api/pull", "POST", { name: modelName });
|
||||
}
|
||||
|
||||
async deleteModel(modelName: string): Promise<void> {
|
||||
await this.request("/api/delete", "DELETE", { name: modelName });
|
||||
}
|
||||
|
||||
async copyModel(sourceModel: string, targetModel: string): Promise<void> {
|
||||
await this.request("/api/copy", "POST", {
|
||||
source: sourceModel,
|
||||
destination: targetModel,
|
||||
});
|
||||
}
|
||||
|
||||
async ping(): Promise<boolean> {
|
||||
try {
|
||||
await this.request("/");
|
||||
return true;
|
||||
} catch {
|
||||
return false;
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -1,22 +1,30 @@
|
||||
import { contextBridge } from 'electron'
|
||||
import { electronAPI } from '@electron-toolkit/preload'
|
||||
import { contextBridge, ipcRenderer } from "electron";
|
||||
import { electronAPI } from "@electron-toolkit/preload";
|
||||
|
||||
// Custom APIs for renderer
|
||||
const api = {}
|
||||
const api = {
|
||||
installOllama: () => ipcRenderer.invoke("install-ollama-and-model"),
|
||||
|
||||
// 监听进度 (Send/On)
|
||||
onInstallProgress: (callback) => {
|
||||
ipcRenderer.on("install-progress", (_event, value) => callback(value));
|
||||
},
|
||||
|
||||
// 移除监听器
|
||||
removeInstallProgressListeners: () => {
|
||||
ipcRenderer.removeAllListeners("install-progress");
|
||||
},
|
||||
};
|
||||
|
||||
// Use `contextBridge` APIs to expose Electron APIs to
|
||||
// renderer only if context isolation is enabled, otherwise
|
||||
// just add to the DOM global.
|
||||
if (process.contextIsolated) {
|
||||
try {
|
||||
contextBridge.exposeInMainWorld('electron', electronAPI)
|
||||
contextBridge.exposeInMainWorld('api', api)
|
||||
contextBridge.exposeInMainWorld("electron", electronAPI);
|
||||
contextBridge.exposeInMainWorld("api", api);
|
||||
} catch (error) {
|
||||
console.error(error)
|
||||
console.error(error);
|
||||
}
|
||||
} else {
|
||||
// @ts-ignore (define in dts)
|
||||
window.electron = electronAPI
|
||||
window.electron = electronAPI;
|
||||
// @ts-ignore (define in dts)
|
||||
window.api = api
|
||||
window.api = api;
|
||||
}
|
||||
|
||||
@@ -19,7 +19,12 @@ const routes: Array<RouteRecordRaw> = [
|
||||
component: () => import("../views/Live/index.vue"),
|
||||
meta: { no_login: true },
|
||||
},
|
||||
// Add more routes as needed
|
||||
{
|
||||
path: "/install",
|
||||
name: "Install",
|
||||
component: () => import("../views/Install/index.vue"),
|
||||
meta: { no_login: true },
|
||||
},
|
||||
];
|
||||
|
||||
export default routes;
|
||||
|
||||
@@ -74,7 +74,7 @@ export const useLiveStore = defineStore("live", () => {
|
||||
|
||||
try {
|
||||
isExplaining.value = true;
|
||||
// TODO: 这里添加讲解岗位的具体实现
|
||||
// 这里添加讲解岗位的具体实现
|
||||
// 可以调用 AI 接口进行讲解
|
||||
const result = await window.electron.ipcRenderer.invoke(
|
||||
"explain-position",
|
||||
@@ -117,7 +117,7 @@ export const useLiveStore = defineStore("live", () => {
|
||||
try {
|
||||
const result = await window.electron.ipcRenderer.invoke(
|
||||
"open-live-window",
|
||||
{ path: "live", width: 375, height: 692, userId: "rs876543" },
|
||||
{ path: "live", width: 375, height: 682 },
|
||||
);
|
||||
if (result.success) {
|
||||
isLiveWindowOpen.value = true;
|
||||
@@ -181,13 +181,11 @@ export const useLiveStore = defineStore("live", () => {
|
||||
positions,
|
||||
(newVal) => {
|
||||
console.log("positions changed:", newVal);
|
||||
// 当添加了新岗位，并且当前没有正在讲解的岗位时，自动开始讲解第一个岗位
|
||||
if (
|
||||
newVal.length > 0 &&
|
||||
!currentPosition.value &&
|
||||
!isExplaining.value
|
||||
) {
|
||||
console.log("Starting next position from positions watch");
|
||||
getNextPosition();
|
||||
}
|
||||
},
|
||||
@@ -215,7 +213,11 @@ export const useLiveStore = defineStore("live", () => {
|
||||
});
|
||||
|
||||
async function jobTransformAIobj(job: any) {
|
||||
const val = await window.electron.ipcRenderer.invoke("ollama-test", job);
|
||||
// const val = await window.electron.ipcRenderer.invoke("ollama-test", job);
|
||||
const val = await window.electron.ipcRenderer.invoke(
|
||||
"run-job-workflow",
|
||||
job,
|
||||
);
|
||||
|
||||
if (val.success === false) {
|
||||
throw new Error(val.error);
|
||||
|
||||
@@ -36,8 +36,9 @@
|
||||
</div>
|
||||
</section>
|
||||
<section class="panel panel-controls">
|
||||
<header class="panel-header">直播控制</header>
|
||||
<header class="panel-header">直播控制：</header>
|
||||
<div class="controls-row">
|
||||
<button @click="loadData">加载数据</button>
|
||||
<button @click="handleOpenLiveWindow">打开直播窗口</button>
|
||||
<button :class="{ 'primary': !isLiveOn }" @click="handleStartLive" :disabled="isLiveOn">
|
||||
开始直播
|
||||
@@ -47,12 +48,24 @@
|
||||
</button>
|
||||
</div>
|
||||
|
||||
<header class="panel-header small">内容控制</header>
|
||||
|
||||
|
||||
<header class="panel-header ">内容控制：</header>
|
||||
<div class="controls-row">
|
||||
<button @click="toggleCameraInsert">全屏插播</button>
|
||||
<button @click="insertCameraVideo">窗口插播</button>
|
||||
<button @click="insertVideoAudio">音频插入</button>
|
||||
</div>
|
||||
|
||||
<header class="panel-header ">工具控制：</header>
|
||||
<div class="controls-row">
|
||||
模型状态：{{ modelStatus }}
|
||||
</div>
|
||||
<div class="controls-row">
|
||||
<button @click="updateStatus">更新状态</button>
|
||||
<button @click="InstallPlugins">安装插件</button>
|
||||
<button @click="startModel">启动模型</button>
|
||||
</div>
|
||||
</section>
|
||||
</div>
|
||||
</div>
|
||||
@@ -66,6 +79,7 @@ import { useUserStore } from '@renderer/stores/useUserStore';
|
||||
import { useLiveStore } from '@renderer/stores/useLiveStore'
|
||||
const { positions, currentPosition, seePosition, isLiveOn } = storeToRefs(useLiveStore())
|
||||
const broadcastOrder = ref([]);
|
||||
const modelStatus = ref('未知')
|
||||
|
||||
onMounted(async () => {
|
||||
init();
|
||||
@@ -73,6 +87,10 @@ onMounted(async () => {
|
||||
})
|
||||
|
||||
async function init() {
|
||||
// useLiveStore().fetchPositions()
|
||||
}
|
||||
|
||||
function loadData() {
|
||||
useLiveStore().fetchPositions()
|
||||
}
|
||||
|
||||
@@ -114,6 +132,45 @@ const handleStopLive = async () => {
|
||||
console.error('结束直播失败:', error)
|
||||
}
|
||||
}
|
||||
|
||||
const InstallPlugins = async () => {
|
||||
try {
|
||||
await window.electron.ipcRenderer.invoke(
|
||||
"open-install-window",
|
||||
{ path: "install", width: 375, height: 692, userId: "rs876543" },
|
||||
);
|
||||
} catch (error) {
|
||||
console.error('安装插件失败:', error)
|
||||
}
|
||||
}
|
||||
|
||||
const updateStatus = async () => {
|
||||
try {
|
||||
const status = await window.electron.ipcRenderer.invoke("check-ollama-status");
|
||||
if (status) {
|
||||
modelStatus.value = '已安装'
|
||||
} else {
|
||||
modelStatus.value = '未安装'
|
||||
}
|
||||
} catch (error) {
|
||||
console.error('更新状态失败:', error)
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
const startModel = async () => {
|
||||
try {
|
||||
const result = await window.electron.ipcRenderer.invoke("ensure-ollama-running");
|
||||
console.log('result', result)
|
||||
if (result.success) {
|
||||
alert(result.message)
|
||||
} else {
|
||||
alert(result.message)
|
||||
}
|
||||
} catch (error) {
|
||||
console.error('更新状态失败:', error)
|
||||
}
|
||||
}
|
||||
function toggleCameraInsert() {
|
||||
window.electron.ipcRenderer.send('toggle-camera-insert')
|
||||
}
|
||||
|
||||
72
src/renderer/src/views/Install/index.vue
Normal file
72
src/renderer/src/views/Install/index.vue
Normal file
@@ -0,0 +1,72 @@
|
||||
<template>
|
||||
<div>
|
||||
<button @click="startInstallation" :disabled="isLoading">
|
||||
{{ isLoading ? '安装中...' : '安装模型 & Qwen3 Modle' }}
|
||||
</button>
|
||||
|
||||
<h3>安装 Log:</h3>
|
||||
<div class="log-container">
|
||||
<pre>{{ log }}</pre>
|
||||
</div>
|
||||
</div>
|
||||
</template>
|
||||
|
||||
<script setup>
|
||||
import { ref, onMounted, onUnmounted } from 'vue';
|
||||
|
||||
const isLoading = ref(false);
|
||||
const log = ref('');
|
||||
|
||||
// 统一处理来自主进程的消息
|
||||
const handleProgress = (progress) => {
|
||||
if (progress.status) {
|
||||
log.value += `\n--- ${progress.status} ---\n`;
|
||||
} else if (progress.type === 'stdout') {
|
||||
log.value += progress.data;
|
||||
} else if (progress.type === 'stderr') {
|
||||
log.value += `[ERROR] ${progress.data}`;
|
||||
}
|
||||
};
|
||||
|
||||
// 启动安装
|
||||
const startInstallation = async () => {
|
||||
isLoading.value = true;
|
||||
log.value = 'Starting installation process...\n';
|
||||
try {
|
||||
const result = await window.api.installOllama();
|
||||
if (result.success) {
|
||||
log.value += `\n--- SUCCESS: ${result.message} ---\n`;
|
||||
} else {
|
||||
log.value += `\n--- FAILED: ${result.message} ---\n`;
|
||||
}
|
||||
} catch (error) {
|
||||
log.value += `\n--- FATAL ERROR: ${error.message} ---\n`;
|
||||
}
|
||||
isLoading.value = false;
|
||||
};
|
||||
|
||||
// 挂载时设置监听器
|
||||
onMounted(() => {
|
||||
window.api.onInstallProgress(handleProgress);
|
||||
});
|
||||
|
||||
// 卸载时清理监听器
|
||||
onUnmounted(() => {
|
||||
window.api.removeInstallProgressListeners();
|
||||
});
|
||||
</script>
|
||||
|
||||
<style scoped>
|
||||
.log-container {
|
||||
background-color: #2b2b2b;
|
||||
color: #f1f1f1;
|
||||
padding: 15px;
|
||||
border-radius: 8px;
|
||||
max-height: 400px;
|
||||
overflow-y: auto;
|
||||
white-space: pre-wrap;
|
||||
/* 自动换行 */
|
||||
word-wrap: break-word;
|
||||
font-family: 'Courier New', Courier, monospace;
|
||||
}
|
||||
</style>
|
||||
@@ -23,11 +23,11 @@ const liveUrl = ref("");
|
||||
const soundUrl = ref("https://dmdemo.hx.cn/sound/welcome.mp3");
|
||||
const welcome = ref()
|
||||
const live = ref()
|
||||
let cameraStream = null // 用于存储摄像头媒体流
|
||||
let cameraStream = null
|
||||
let wasWelcomePlaying = false
|
||||
const cameraVideo = ref()
|
||||
const liveIframe = ref(null) // 对应模板中的 iframe
|
||||
const micAudio = ref(null) // 隐藏的麦克风播放元素
|
||||
const liveIframe = ref(null)
|
||||
const micAudio = ref(null)
|
||||
let micStream = null
|
||||
let prevIframeVideoVolume = 1
|
||||
let micPlaying = false
|
||||
@@ -45,7 +45,6 @@ function welcomeEnd() {
|
||||
}
|
||||
}
|
||||
} catch (e) {
|
||||
// 可能跨域，忽略
|
||||
}
|
||||
}
|
||||
|
||||
@@ -73,7 +72,6 @@ onBeforeUnmount(() => {
|
||||
})
|
||||
|
||||
function startLive() {
|
||||
// 从 URL 获取 userId
|
||||
const paramsUserId = route.query.userId;
|
||||
if (paramsUserId) {
|
||||
userId.value = paramsUserId
|
||||
@@ -83,10 +81,8 @@ function startLive() {
|
||||
|
||||
async function handleInsertCameraVideo() {
|
||||
if (isCameraActive.value) {
|
||||
// 停止摄像头
|
||||
stopCamera()
|
||||
} else {
|
||||
// 启动摄像头
|
||||
await startCamera()
|
||||
}
|
||||
}
|
||||
|
||||
@@ -2,7 +2,7 @@
|
||||
"extends": "@electron-toolkit/tsconfig/tsconfig.web.json",
|
||||
"include": [
|
||||
"src/renderer/src/env.d.ts",
|
||||
"src/renderer/src/**/*",
|
||||
"src/renderer/src/**/*.ts",
|
||||
"src/renderer/src/**/*.vue",
|
||||
"src/preload/*.d.ts"
|
||||
],
|
||||
@@ -13,6 +13,7 @@
|
||||
"@renderer/*": [
|
||||
"src/renderer/src/*"
|
||||
]
|
||||
}
|
||||
},
|
||||
"allowJs": true
|
||||
}
|
||||
}
|
||||
|
||||
Reference in New Issue
Block a user