/**
 * @file AssistantManager.ts
 * @description This file defines the AssistantManager class, responsible for managing various
 * API routes related to the Assistant functionality. It provides features such as file handling,
 * web scraping, and integration with third-party APIs like OpenAI and Google Custom Search.
 * It also handles job tracking and progress reporting for tasks like document creation and web scraping.
 * Utility functions for path manipulation and file operations are included, along with
 * a mechanism for handling retry logic during API calls.
 */

import { Readability } from '@mozilla/readability';
import axios from 'axios';
import { spawn } from 'child_process';
import * as fs from 'fs';
import { writeFile } from 'fs';
import { google } from 'googleapis';
import { JSDOM } from 'jsdom';
import OpenAI from 'openai';
import * as path from 'path';
import * as puppeteer from 'puppeteer';
import { promisify } from 'util';
import * as uuid from 'uuid';
import { AI_Document } from '../../client/views/nodes/chatbot/types/types';
import { DashUploadUtils } from '../DashUploadUtils';
import { Method } from '../RouteManager';
import { filesDirectory, publicDirectory } from '../SocketData';
import ApiManager, { Registration } from './ApiManager';
import { env } from 'process';

// Enumeration of directories where different file types are stored
export enum Directory {
    parsed_files = 'parsed_files',
    images = 'images',
    videos = 'videos',
    pdfs = 'pdfs',
    text = 'text',
    pdf_thumbnails = 'pdf_thumbnails',
    audio = 'audio',
    csv = 'csv',
    chunk_images = 'chunk_images',
    scrape_images = 'scrape_images',
}

// In-memory job tracking
const jobResults: { [key: string]: unknown } = {};
const jobProgress: { [key: string]: unknown } = {};

/**
 * Constructs a normalized path to a file in the server's file system.
 * @param directory The directory where the file is stored.
 * @param filename The name of the file.
 * @returns The full normalized path to the file.
 */
export function serverPathToFile(directory: Directory, filename: string) {
    return path.normalize(`${filesDirectory}/${directory}/${filename}`);
}

/**
 * Constructs a normalized path to a directory in the server's file system.
 * @param directory The directory to access.
 * @returns The full normalized path to the directory.
 */
export function pathToDirectory(directory: Directory) {
    return path.normalize(`${filesDirectory}/${directory}`);
}

/**
 * Constructs the client-accessible URL for a file.
 * @param directory The directory where the file is stored.
 * @param filename The name of the file.
 * @returns The URL path to the file.
 */
export function clientPathToFile(directory: Directory, filename: string) {
    return `/files/${directory}/${filename}`;
}

// Promisified versions of filesystem functions
const writeFileAsync = promisify(writeFile);
const readFileAsync = promisify(fs.readFile);

/**
 * Class responsible for handling various API routes related to the Assistant functionality.
 * This class extends `ApiManager` and handles registration of routes and secure request handlers.
 */
export default class AssistantManager extends ApiManager {
    /**
     * Registers all API routes and initializes necessary services like OpenAI and Google Custom Search.
     * @param register The registration method to register routes and handlers.
     */
    protected initialize(register: Registration): void {
        // Initialize Google Custom Search API
        const customsearch = google.customsearch('v1');
        const openai = new OpenAI({ apiKey: env.OPENAI_API_KEY });

        // Register Wikipedia summary API route
        register({
            method: Method.POST,
            subscription: '/getWikipediaSummary',
            secureHandler: async ({ req, res }) => {
                const { title } = req.body;
                try {
                    // Fetch summary from Wikipedia using axios
                    const response = await axios.get('https://en.wikipedia.org/w/api.php', {
                        params: {
                            action: 'query',
                            list: 'search',
                            srsearch: title,
                            format: 'json',
                        },
                    });
                    const summary = response.data.query.search[0]?.snippet || 'No article found with that title.';
                    res.send({ text: summary });
                } catch (error) {
                    console.error('Error retrieving Wikipedia summary:', error);
                    res.status(500).send({
                        error: 'Error retrieving article summary from Wikipedia.',
                    });
                }
            },
        });

        // Register an API route to retrieve web search results using Google Custom Search
        // This route filters results by checking their x-frame-options headers for security purposes
        register({
            method: Method.POST,
            subscription: '/getWebSearchResults',
            secureHandler: async ({ req, res }) => {
                const { query, max_results } = req.body;
                const MIN_VALID_RESULTS_RATIO = 0.75; // 3/4 threshold
                let startIndex = 1; // Start at the first result initially
                const fetchSearchResults = async (start: number) => {
                    return customsearch.cse.list({
                        q: query,
                        cx: process.env._CLIENT_GOOGLE_SEARCH_ENGINE_ID,
                        key: process.env._CLIENT_GOOGLE_API_KEY,
                        safe: 'active',
                        num: max_results,
                        start, // This controls which result index the search starts from
                    });
                };

                const filterResultsByXFrameOptions = async (
                    results: {
                        url: string | null | undefined;
                        snippet: string | null | undefined;
                    }[]
                ) => {
                    const filteredResults = await Promise.all(
                        results
                            .filter(result => result.url)
                            .map(async result => {
                                try {
                                    const urlResponse = await axios.head(result.url!, { timeout: 5000 });
                                    const xFrameOptions = urlResponse.headers['x-frame-options'];
                                    if (xFrameOptions && xFrameOptions.toUpperCase() === 'SAMEORIGIN') {
                                        return result;
                                    }
                                } catch (error) {
                                    console.error(`Error checking x-frame-options for URL: ${result.url}`, error);
                                }
                                return null; // Exclude the result if it doesn't match
                            })
                    );
                    return filteredResults.filter(result => result !== null); // Remove null results
                };

                try {
                    // Fetch initial search results
                    let response = await fetchSearchResults(startIndex);
                    const initialResults =
                        response.data.items?.map(item => ({
                            url: item.link,
                            snippet: item.snippet,
                        })) || [];

                    // Filter the initial results
                    let validResults = await filterResultsByXFrameOptions(initialResults);

                    // If valid results are less than 3/4 of max_results, fetch more results
                    while (validResults.length < max_results * MIN_VALID_RESULTS_RATIO) {
                        // Increment the start index by the max_results to fetch the next set of results
                        startIndex += max_results;
                        response = await fetchSearchResults(startIndex);

                        const additionalResults =
                            response.data.items?.map(item => ({
                                url: item.link,
                                snippet: item.snippet,
                            })) || [];

                        const additionalValidResults = await filterResultsByXFrameOptions(additionalResults);
                        validResults = [...validResults, ...additionalValidResults]; // Combine valid results

                        // Break if no more results are available
                        if (additionalValidResults.length === 0 || response.data.items?.length === 0) {
                            break;
                        }
                    }

                    // Return the filtered valid results
                    res.send({ results: validResults.slice(0, max_results) }); // Limit the results to max_results
                } catch (error) {
                    console.error('Error performing web search:', error);
                    res.status(500).send({
                        error: 'Failed to perform web search',
                    });
                }
            },
        });

        /**
         * Converts a video file to audio format using ffmpeg.
         * @param videoPath The path to the input video file.
         * @param outputAudioPath The path to the output audio file.
         * @returns A promise that resolves when the conversion is complete.
         */
        function convertVideoToAudio(videoPath: string, outputAudioPath: string): Promise<void> {
            return new Promise((resolve, reject) => {
                const ffmpegProcess = spawn('ffmpeg', [
                    '-i',
                    videoPath, // Input file
                    '-vn', // No video
                    '-acodec',
                    'pcm_s16le', // Audio codec
                    '-ac',
                    '1', // Number of audio channels
                    '-ar',
                    '16000', // Audio sampling frequency
                    '-f',
                    'wav', // Output format
                    outputAudioPath, // Output file
                ]);

                ffmpegProcess.on('error', error => {
                    console.error('Error running ffmpeg:', error);
                    reject(error);
                });

                ffmpegProcess.on('close', code => {
                    if (code === 0) {
                        console.log('Audio extraction complete:', outputAudioPath);
                        resolve();
                    } else {
                        reject(new Error(`ffmpeg exited with code ${code}`));
                    }
                });
            });
        }

        // Register an API route to process a media file (audio or video)
        // Extracts audio from video files, transcribes the audio using OpenAI Whisper, and provides a summary
        register({
            method: Method.POST,
            subscription: '/processMediaFile',
            secureHandler: async ({ req, res }) => {
                const { fileName } = req.body;

                // Ensure the filename is provided
                if (!fileName) {
                    res.status(400).send({ error: 'Filename is required' });
                    return;
                }

                try {
                    // Determine the file type and location
                    const isAudio = fileName.toLowerCase().endsWith('.mp3');
                    const directory = isAudio ? Directory.audio : Directory.videos;
                    const filePath = serverPathToFile(directory, fileName);

                    // Check if the file exists
                    if (!fs.existsSync(filePath)) {
                        res.status(404).send({ error: 'File not found' });
                        return;
                    }

                    console.log(`Processing ${isAudio ? 'audio' : 'video'} file: ${fileName}`);

                    // Step 1: Extract audio if it's a video
                    let audioPath = filePath;
                    if (!isAudio) {
                        const audioFileName = `${path.basename(fileName, path.extname(fileName))}.wav`;
                        audioPath = path.join(pathToDirectory(Directory.audio), audioFileName);

                        console.log('Extracting audio from video...');
                        await convertVideoToAudio(filePath, audioPath);
                    }

                    // Step 2: Transcribe audio using OpenAI Whisper
                    console.log('Transcribing audio...');
                    const transcription = await openai.audio.transcriptions.create({
                        file: fs.createReadStream(audioPath),
                        model: 'whisper-1',
                        response_format: 'verbose_json',
                        timestamp_granularities: ['segment'],
                    });

                    console.log('Audio transcription complete.');

                    // Step 3: Extract concise JSON
                    console.log('Extracting concise JSON...');
                    const originalSegments = transcription.segments?.map((segment, index) => ({
                        index: index.toString(),
                        text: segment.text,
                        start: segment.start,
                        end: segment.end,
                    }));

                    interface ConciseSegment {
                        text: string;
                        indexes: string[];
                        start: number | null;
                        end: number | null;
                    }

                    const combinedSegments = [];
                    let currentGroup: ConciseSegment = { text: '', indexes: [], start: null, end: null };
                    let currentDuration = 0;

                    originalSegments?.forEach(segment => {
                        const segmentDuration = segment.end - segment.start;

                        if (currentDuration + segmentDuration <= 4000) {
                            // Add segment to the current group
                            currentGroup.text += (currentGroup.text ? ' ' : '') + segment.text;
                            currentGroup.indexes.push(segment.index);
                            if (currentGroup.start === null) {
                                currentGroup.start = segment.start;
                            }
                            currentGroup.end = segment.end;
                            currentDuration += segmentDuration;
                        } else {
                            // Push the current group and start a new one
                            combinedSegments.push({ ...currentGroup });
                            currentGroup = {
                                text: segment.text,
                                indexes: [segment.index],
                                start: segment.start,
                                end: segment.end,
                            };
                            currentDuration = segmentDuration;
                        }
                    });

                    // Push the final group if it has content
                    if (currentGroup.text) {
                        combinedSegments.push({ ...currentGroup });
                    }
                    const lastSegment = combinedSegments[combinedSegments.length - 1];

                    // Check if the last segment is too short and combine it with the second last
                    if (combinedSegments.length > 1 && lastSegment.end && lastSegment.start) {
                        const secondLastSegment = combinedSegments[combinedSegments.length - 2];
                        const lastDuration = lastSegment.end - lastSegment.start;

                        if (lastDuration < 30) {
                            // Combine the last segment with the second last
                            secondLastSegment.text += (secondLastSegment.text ? ' ' : '') + lastSegment.text;
                            secondLastSegment.indexes = secondLastSegment.indexes.concat(lastSegment.indexes);
                            secondLastSegment.end = lastSegment.end;

                            // Remove the last segment from the array
                            combinedSegments.pop();
                        }
                    }

                    console.log('Segments combined successfully.');

                    console.log('Generating summary using GPT-4...');
                    const combinedText = combinedSegments.map(segment => segment.text).join(' ');

                    let summary = '';
                    try {
                        const completion = await openai.chat.completions.create({
                            messages: [{ role: 'system', content: `Summarize the following text in a concise paragraph:\n\n${combinedText}` }],
                            model: 'gpt-4o',
                        });
                        console.log('Summary generation complete.');
                        summary = completion.choices[0].message.content ?? 'Summary could not be generated.';
                    } catch (summaryError) {
                        console.error('Error generating summary:', summaryError);
                        summary = 'Summary could not be generated.';
                    }
                    // Step 5: Return the JSON result
                    res.send({ full: originalSegments, condensed: combinedSegments, summary });
                } catch (error) {
                    console.error('Error processing media file:', error);
                    res.status(500).send({ error: 'Failed to process media file' });
                }
            },
        });

        // Axios instance with custom headers for scraping
        const axiosInstance = axios.create({
            headers: {
                'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36',
            },
        });

        /**
         * Utility function to introduce delay (used for retries).
         * @param ms Delay in milliseconds.
         */
        const delay = (ms: number) => new Promise(resolve => setTimeout(resolve, ms));

        /**
         * Function to fetch a URL with retry logic, handling rate limits.
         * Retries a request if it fails due to rate limits (HTTP status 429).
         * @param url The URL to fetch.
         * @param retries The number of retry attempts.
         * @param backoff Initial backoff time in milliseconds.
         */
        const fetchWithRetry = async (url: string, retries = 3, backoff = 300): Promise<unknown> => {
            try {
                const response = await axiosInstance.get(url);
                return response.data;
            } catch (error) {
                if (retries > 0 && (error as { response: { status: number } }).response?.status === 429) {   // bcz: don't know the error type
                    console.log(`Rate limited. Retrying in ${backoff}ms...`);
                    await delay(backoff);
                    return fetchWithRetry(url, retries - 1, backoff * 2);
                } // prettier-ignore
                throw error;
            }
        };

        // Register an API route to generate an image using OpenAI's DALL-E model
        // Uploads the generated image to the server and provides a URL for access
        register({
            method: Method.POST,
            subscription: '/generateImage',
            secureHandler: async ({ req, res }) => {
                const { image_prompt } = req.body;

                if (!image_prompt) {
                    res.status(400).send({ error: 'No prompt provided' });
                    return;
                }

                try {
                    const image = await openai.images.generate({ model: 'dall-e-3', prompt: image_prompt, response_format: 'url' });
                    console.log(image);
                    const url = image.data?.[0].url;

                    const result = url ? await DashUploadUtils.UploadImage(url) : { error: 'Image generation failed' };

                    res.send({ result, url });
                } catch (error) {
                    console.error('Error fetching the URL:', error);
                    res.status(500).send({
                        error: 'Failed to fetch the URL',
                    });
                }
            },
        });

        // Register an API route to fetch data from a URL using a proxy with retry logic
        // Useful for bypassing rate limits or scraping inaccessible data
        register({
            method: Method.POST,
            subscription: '/proxyFetch',
            secureHandler: async ({ req, res }) => {
                const { url } = req.body;

                if (!url) {
                    res.status(400).send({ error: 'No URL provided' });
                    return;
                }

                try {
                    const data = await fetchWithRetry(url);
                    res.send({ data });
                } catch (error) {
                    console.error('Error fetching the URL:', error);
                    res.status(500).send({
                        error: 'Failed to fetch the URL',
                    });
                }
            },
        });

        // Register an API route to scrape website content using Puppeteer and JSDOM
        // Extracts and returns readable content from a given URL
        register({
            method: Method.POST,
            subscription: '/scrapeWebsite',
            secureHandler: async ({ req, res }) => {
                const { url } = req.body;
                try {
                    // Launch Puppeteer browser to navigate to the webpage
                    const browser = await puppeteer.launch({
                        args: ['--no-sandbox', '--disable-setuid-sandbox'],
                    });
                    const page = await browser.newPage();
                    await page.setUserAgent('Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36');
                    await page.goto(url, { waitUntil: 'networkidle2' });

                    // Extract HTML content
                    const htmlContent = await page.content();
                    await browser.close();

                    // Parse HTML content using JSDOM
                    const dom = new JSDOM(htmlContent, { url });

                    // Extract readable content using Mozilla's Readability API
                    const reader = new Readability(dom.window.document);
                    const article = reader.parse();

                    if (article) {
                        const plainText = article.textContent;
                        res.send({ website_plain_text: plainText });
                    } else {
                        res.status(500).send({ error: 'Failed to extract readable content' });
                    }
                } catch (error) {
                    console.error('Error scraping website:', error);
                    res.status(500).send({
                        error: 'Failed to scrape website',
                    });
                }
            },
        });

        // Register an API route to create a document and start a background job for processing
        // Uses Python scripts to process files and generate document chunks for further use
        register({
            method: Method.POST,
            subscription: '/createDocument',
            secureHandler: async ({ req, res }) => {
                const { file_path } = req.body;
                const public_path = path.join(publicDirectory, file_path); // Resolve the file path in the public directory
                const file_name = path.basename(file_path); // Extract the file name from the path

                try {
                    // Read the file data and encode it as base64
                    const file_data = fs.readFileSync(public_path, { encoding: 'base64' });

                    // Generate a unique job ID for tracking
                    const jobId = uuid.v4();

                    // Spawn the Python process and track its progress/output
                    // eslint-disable-next-line no-use-before-define
                    spawnPythonProcess(jobId, public_path);

                    // Send the job ID back to the client for tracking
                    res.send({ jobId });
                } catch (error) {
                    console.error('Error initiating document creation:', error);
                    res.status(500).send({
                        error: 'Failed to initiate document creation',
                    });
                }
            },
        });

        // Register an API route to check the progress of a document creation job
        // Returns the current step and progress percentage
        register({
            method: Method.GET,
            subscription: '/getProgress/:jobId',
            secureHandler: async ({ req, res }) => {
                const { jobId } = req.params; // Get the job ID from the URL parameters
                // Check if the job progress is available
                if (jobProgress[jobId]) {
                    res.json(jobProgress[jobId]);
                } else {
                    res.json({
                        step: 'Processing Document...',
                        progress: '0',
                    });
                }
            },
        });

        // Register an API route to retrieve the final result of a document creation job
        // Returns the processed data or an error status if the job is incomplete
        register({
            method: Method.GET,
            subscription: '/getResult/:jobId',
            secureHandler: async ({ req, res }) => {
                const { jobId } = req.params;
                if (jobResults[jobId]) {
                    const result = jobResults[jobId] as AI_Document & { status: string };

                    if (result.chunks && Array.isArray(result.chunks)) {
                        result.status = 'completed';
                    } else {
                        result.status = 'pending';
                    }
                    res.json(result);
                } else {
                    res.status(202).send({ status: 'pending' });
                }
            },
        });

        // Register an API route to format chunks of text or images for structured display
        // Converts raw chunk data into a structured format for frontend consumption
        register({
            method: Method.POST,
            subscription: '/formatChunks',
            secureHandler: async ({ req, res }) => {
                const { relevantChunks } = req.body; // Get the relevant chunks from the request body

                // Initialize an array to hold the formatted content
                const content: { type: string; text?: string; image_url?: { url: string } }[] = [{ type: 'text', text: '<chunks>' }];

                await Promise.all(
                    relevantChunks.map((chunk: { id: string; metadata: { type: string; text: TimeRanges; file_path: string } }) => {
                        // Format each chunk by adding its metadata and content
                        content.push({
                            type: 'text',
                            text: `<chunk chunk_id=${chunk.id} chunk_type="${chunk.metadata.type}">`,
                        });

                        // If the chunk is an image or table, read the corresponding file and encode it as base64
                        if (chunk.metadata.type === 'image' || chunk.metadata.type === 'table') {
                            try {
                                const filePath = path.join(pathToDirectory(Directory.chunk_images), chunk.metadata.file_path); // Get the file path
                                console.log(filePath);
                                readFileAsync(filePath).then(imageBuffer => {
                                    const base64Image = imageBuffer.toString('base64'); // Convert the image to base64

                                    // Add the base64-encoded image to the content array
                                    if (base64Image) {
                                        content.push({
                                            type: 'image_url',
                                            image_url: {
                                                url: `data:image/jpeg;base64,${base64Image}`,
                                            },
                                        });
                                    } else {
                                        console.log(`Failed to encode image for chunk ${chunk.id}`);
                                    }
                                });
                            } catch (error) {
                                console.error(`Error reading image file for chunk ${chunk.id}:`, error);
                            }
                        }

                        // Add the chunk's text content to the formatted content
                        content.push({ type: 'text', text: `${chunk.metadata.text}\n</chunk>\n` });
                    })
                );

                content.push({ type: 'text', text: '</chunks>' });

                // Send the formatted content back to the client
                res.send({ formattedChunks: content });
            },
        });

        // Register an API route to create and save a CSV file on the server
        // Writes the CSV content to a unique file and provides a URL for download
        register({
            method: Method.POST,
            subscription: '/createCSV',
            secureHandler: async ({ req, res }) => {
                const { filename, data } = req.body;

                // Validate that both the filename and data are provided
                if (!filename || !data) {
                    res.status(400).send({ error: 'Filename and data fields are required.' });
                    return;
                }

                try {
                    // Generate a UUID for the file to ensure unique naming
                    const uuidv4 = uuid.v4();
                    const fullFilename = `${uuidv4}-${filename}`; // Prefix the file name with the UUID

                    // Get the full server path where the file will be saved
                    const serverFilePath = serverPathToFile(Directory.csv, fullFilename);

                    // Write the CSV data (which is a raw string) to the file
                    await writeFileAsync(serverFilePath, data, 'utf8');

                    // Construct the client-accessible URL for the file
                    const fileUrl = clientPathToFile(Directory.csv, fullFilename);

                    // Send the file URL and UUID back to the client
                    res.send({ fileUrl, id: uuidv4 });
                } catch (error) {
                    console.error('Error creating CSV file:', error);
                    res.status(500).send({
                        error: 'Failed to create CSV file.',
                    });
                }
            },
        });
    }
}

/**
 * Spawns a Python process to handle file processing tasks.
 * @param jobId The job ID for tracking progress.
 * @param file_name The name of the file to process.
 * @param file_path The filepath of the file to process.
 */
function spawnPythonProcess(jobId: string, file_path: string) {
    const venvPath = path.join(__dirname, '../chunker/venv');
    const requirementsPath = path.join(__dirname, '../chunker/requirements.txt');
    const pythonScriptPath = path.join(__dirname, '../chunker/pdf_chunker.py');

    const outputDirectory = pathToDirectory(Directory.chunk_images);

    function runPythonScript() {
        const pythonPath = process.platform === 'win32' ? path.join(venvPath, 'Scripts', 'python') : path.join(venvPath, 'bin', 'python3');

        const pythonProcess = spawn(pythonPath, [pythonScriptPath, jobId, file_path, outputDirectory]);

        let pythonOutput = '';
        let stderrOutput = '';

        pythonProcess.stdout.on('data', data => {
            pythonOutput += data.toString();
        });

        pythonProcess.stderr.on('data', data => {
            stderrOutput += data.toString();
            const lines = stderrOutput.split('\n');
            stderrOutput = lines.pop() || ''; // Save the last partial line back to stderrOutput
            lines.forEach(line => {
                if (line.trim()) {
                    if (line.startsWith('PROGRESS:')) {
                        const jsonString = line.substring('PROGRESS:'.length);
                        try {
                            const parsedOutput = JSON.parse(jsonString);
                            if (parsedOutput.job_id && parsedOutput.progress !== undefined) {
                                jobProgress[parsedOutput.job_id] = {
                                    step: parsedOutput.step,
                                    progress: parsedOutput.progress,
                                };
                            } else if (parsedOutput.progress !== undefined) {
                                jobProgress[jobId] = {
                                    step: parsedOutput.step,
                                    progress: parsedOutput.progress,
                                };
                            }
                        } catch (err) {
                            console.error('Error parsing progress JSON:', jsonString, err);
                        }
                    } else {
                        // Log other stderr output
                        console.error('Python stderr:', line);
                    }
                }
            });
        });

        pythonProcess.on('close', code => {
            if (code === 0) {
                try {
                    const finalResult = JSON.parse(pythonOutput);
                    jobResults[jobId] = finalResult;
                    jobProgress[jobId] = { step: 'Complete', progress: 100 };
                } catch (err) {
                    console.error('Error parsing final JSON result:', err);
                    jobResults[jobId] = { error: 'Failed to parse final result' };
                }
            } else {
                console.error(`Python process exited with code ${code}`);
                // Check if there was an error message in stderr
                if (stderrOutput) {
                    // Try to parse the last line as JSON
                    const lines = stderrOutput.trim().split('\n');
                    const lastLine = lines[lines.length - 1];
                    try {
                        const errorOutput = JSON.parse(lastLine);
                        jobResults[jobId] = errorOutput;
                    } catch {
                        jobResults[jobId] = { error: 'Python process failed' };
                    }
                } else {
                    jobResults[jobId] = { error: 'Python process failed' };
                }
            }
        });
    }
    // Check if venv exists
    if (!fs.existsSync(venvPath)) {
        console.log('Virtual environment not found. Creating and setting up...');

        // Create venv
        // const createVenvProcess = spawn('python', ['-m', 'venv', venvPath]);
        const createVenvProcess = spawn('python3.10', ['-m', 'venv', venvPath]);

        createVenvProcess.on('close', code => {
            if (code !== 0) {
                console.error(`Failed to create virtual environment. Exit code: ${code}`);
                return;
            }

            console.log('Virtual environment created. Installing requirements...');

            // Determine the pip path based on the OS
            const pipPath = process.platform === 'win32' ? path.join(venvPath, 'Scripts', 'pip.exe') : path.join(venvPath, 'bin', 'pip3'); // Try 'pip3' for Unix-like systems

            if (!fs.existsSync(pipPath)) {
                console.error(`pip executable not found at ${pipPath}`);
                return;
            }

            // Install requirements
            const installRequirementsProcess = spawn(pipPath, ['install', '-r', requirementsPath]);

            installRequirementsProcess.stdout.on('data', data => {
                console.log(`pip stdout: ${data}`);
            });

            installRequirementsProcess.stderr.on('data', data => {
                console.error(`pip stderr: ${data}`);
            });

            installRequirementsProcess.on('error', error => {
                console.error(`Error starting pip process: ${error}`);
            });

            installRequirementsProcess.on('close', closecode => {
                if (closecode !== 0) {
                    console.error(`Failed to install requirements. Exit code: ${closecode}`);
                    return;
                }

                console.log('Requirements installed. Running Python script...');
                runPythonScript();
            });
        });
    } else {
        console.log('Virtual environment found. Running Python script...');
        runPythonScript();
    }
}