// Loading required packages
require("./requires.js")
console.log(start);
 
 
// Initialising map to be used to store the functionality later on for reloadability
mapFunctions = new Map()
 
 
// Loading the Function Map
var path = `${mainDir}/services/modules`
var folders = fs.readdirSync(path).filter(function (file) {
    return fs.statSync(path+'/'+file).isDirectory();
});
folders.forEach(element => {
    var commandFiles = fs.readdirSync(`${path}/${element}`).filter(file => file.endsWith('.js') && !file.startsWith("index"));
    for (const file of commandFiles) {
        delete require.cache[require.resolve(`${path}/${element}/${file}`)];
        const command = require(`${path}/${element}/${file}`);
        mapFunctions.set(command.name, command);
    }
});
 
 
 
// The startup information for the project, here you can add stuff that might be nice to see when the app starts
mapFunctions.get("Startup_function").function()
console.log("------------------------------------ Status ------------------------------------");
console.log(__dirname);
console.log(platform);
console.log(`The Startup took ${new Date() - start}ms`)
console.log(`${mapFunctions.size} Function modules loaded`);
console.log("--------------------------------------------------------------------------------");
 
 
 
 
 
 
// --------------------------------------------------------- CLI COMMANDS --------------------------------------------------------- //
 
const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout
});
 
 
rl.on("line", data =>{
    const args = data.trim().split(" ");
    const command = args.shift().toLowerCase();
    mapFunctions.get("cliCommands").function(command, args)
})
 
 
 
 
 
// ----------------------------------------------------------- ELECTRON ----------------------------------------------------------- //
 
let mainWindow;
 
function createWindow() {
    mainWindow = new electron.BrowserWindow({
        width: 1200,
        height: 800,
        webPreferences: {
            nodeIntegration: false,
            contextIsolation: true,
            preload: `${mainDir}/electron/main/preload.js`
        }
    });
 
    mainWindow.loadFile('./electron/main/index.html');
}
 
electron.app.whenReady().then(createWindow);
 
 
// electron.ipcMain.on("extract", (event, args) => {
//     mapFunctions.get("extraction-video-to-audio").function(args)
// })
 
// setTimeout(() => {
//     mainWindow.webContents.send("fuck", "worked uwu")
// }, 5000);
 
electron.ipcMain.handle('get-module-names', async () => {
    let module_array = {
        "ai_modules":[],
        "transcription_modules":[]
    }
    mapFunctions.forEach(e => {
        switch(e.type){
            case "llm":
                module_array.ai_modules.push({"name": e.name, "displayname": e.displayname})
                break;
            case "transcription":
                module_array.transcription_modules.push({"name": e.name, "displayname": e.displayname})
                break;
        }
    })
    // console.log(module_array);
    return module_array
});
 
 
// electron.ipcMain.on("get_modules", async (event, args) => {
//     let module_array = {
//         "ai_modules":[],
//         "transcription_modules":[]
//     }
//     mapFunctions.forEach(e => {
//         switch(e.type){
//             case "llm":
//                 module_array.ai_modules.push({"name": e.name, "displayname": e.displayname})
//                 break;
//             case "transcription":
//                 module_array.transcription_modules.push({"name": e.name, "displayname": e.displayname})
//                 break;
//         }
//     })
//     console.log(module_array);
 
//     mainWindow.webContents.send("modules", module_array)
// })
 
 
 
electron.ipcMain.on("file_submit", async (event, args) => {
    try {
        globalArgs = args
        let curstep = 0
        let totalsteps = 4
 
        const TEMPLATE_MAP = {
            "followup-report": "followup_report.txt",
            "agenda": "agenda.txt",
            "result-protocol": "result_protocol.txt",
            "sprint-planning": "sprint_planning_note.txt",
            "custom": "custom_document.txt"
        };
 
        const templateFile = TEMPLATE_MAP[args.document.type];
 
        if (!templateFile) {
            throw new Error("Unknown document type: " + args.document.type);
        }
 
        console.log(args);
        let audiopath = ""
        let transcriptpath = ""
 
        console.log("\n\n Running the Video to Audio Extractor");
        // This code handles the Video to Audio extraction module call
        await mapFunctions.get("module-handler").function(args.video.module, {inputVideoPath: args.video.inputVideoPath, outputType: mapFunctions.get(args.transcription.module).audioformat}).then(resp => {
            console.log(resp);
            audiopath = resp
            curstep++
            mainWindow.webContents.send("progress", {curstep:curstep, totalsteps:totalsteps})
        }).catch(err => {
            mainWindow.webContents.send("error", err)
            return
        })
 
 
        console.log("\n\n Running the Audio to Transcription module");
        // TODO implement transcription module
        // This code handles the Audio to Text transcription module call
        await mapFunctions.get("module-handler").function(args.transcription.module, audiopath).then(resp => {
            console.log(resp);
            transcriptpath = resp
            curstep++
            mainWindow.webContents.send("progress", {curstep:curstep, totalsteps:totalsteps})
        }).catch(err => {
            mainWindow.webContents.send("error", err)
            return
        })
 
 
        console.log("\n\n Running the Transcription Summarizer module");
        // This code summarises the transcript, so that it can be used by an llm
        // await mapFunctions.get("summarize-transcription").function('A:\\programing\\@projects\\video2document\\storage\\transcripts\\IMG_2978.json').then(resp => {
        await mapFunctions.get("summarize-transcription2").function(transcriptpath).then(resp => {
            console.log(resp);
            transcriptpath = resp
            curstep++
            mainWindow.webContents.send("progress", {curstep:curstep, totalsteps:totalsteps})
        }).catch(err => {
            mainWindow.webContents.send("error", err)
            return
        })
 
        console.log("\n\n Running the LLM module");
        // TODO implement documentation module
        // This code handles the Text to Document processing module call
        
        console.log(`\n\n Running the LLM for Document Style ${args.document.type}`);
 
        await mapFunctions.get("module-handler").function(args.document.module, { inputTranscriptPath: transcriptpath, documentTypePath: "./storage/documentType/" + templateFile, language: "en" }).then(resp => {
            console.log(resp);
            transcriptpath = resp
            curstep++
            mainWindow.webContents.send("progress", { curstep: curstep, totalsteps: totalsteps })
        }).catch(err => {
            mainWindow.webContents.send("error", err)
            return
        })
        
 
        // TODO actually implement this functionality
        // Module to get the first few lines for each speaker to send to the frontend
//         await mapFunctions.get("speaker-getter-idfk").function(transcriptpath).then(resp => {
//             console.log(resp);
//             transcriptpath = resp
//             curstep++
//             mainWindow.webContents.send("progress", {curstep:curstep, totalsteps:totalsteps})
 
// // {
// // speakerA: {source: "Pfad zur Audio File"},
// // speakerB:.....
// // }
            mainWindow.webContents.send("speakers", {speakerA:"pfad1", speakerB:"pfad2"})
//         }).catch(err => {
//             mainWindow.webContents.send("error", err)
//             return
//         })
 
 
    } catch (error) {
        console.log(error);
    }
})
 
 
 
let q =
{
    video: {
        module: "String", // The name of the module, idk if we ever implement other extraction modules, the default one is extraction-video-to-audio
        inputVideoPath: "String", // See script.js on line 27 for an example of what this should look like
        outputType: "String" // The file format to be used for the audio output file, such as wav, mp3, flac and so on
    },
    transcription:{
        module: "String" // The module name of the transcription model you want to use
    },
    document:{
        module: "String", // The module name of the AI model you want to use to create the document
        styles: [ // An array of all the document styles/prompts you want to have the document be processed with
            {
                prompt: "String",
            }
        ]
    }
}
 
 
let q1 = {
    "ai_modules":    [
        {name:"abc", displayname:"ABC"},
        {name:"qeg", displayname:"aqghegahu"}
    ],
    "transcription_modules":    [
        {name:"abc", displayname:"ABC"},
        {name:"qeg", displayname:"aqghegahu"}
    ]
}