Lielais Cibas Filtrs

LCF.user.js

// ==UserScript==
// @name         LCF
// @namespace    https://gist.github.com/mindbound
// @version      0.5.4
// @description  Applies user-defined filters to the latest posts page
// @author       mindbound
// @license      WTFPL; http://www.wtfpl.net/
// @match        http://klab.lv/stats/latest.bml
// @icon         data:image/png;base64,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
// @connect      https://raw.githubusercontent.com
// @connect      https://cdn.jsdelivr.net
// @require      https://raw.githubusercontent.com/mindbound/GM_config/master/gm_config.js
// @require      https://cdn.jsdelivr.net/npm/@tensorflow/tfjs@latest/dist/tf.min.js
// @grant        GM_xmlhttpRequest
// @grant        GM_getValue
// @grant        GM_setValue
// @grant        GM_registerMenuCommand
// @run-at       document-end
// ==/UserScript==

"use strict";

let model;
let isTFBackendInitialized = false;

const MODEL_NAME = "LCF";
const MODEL_URL = "https://raw.githubusercontent.com/mindbound/LCF/master/model/model.json";
const MODEL_VERSION_URL = "https://raw.githubusercontent.com/mindbound/LCF/master/model/model_version.txt"
const MODEL_PROD = true;

const chars = "abcdefghijklmnopqrstuvwxyz0123456789_";
const charToInt = {};

for (let i = 0; i < chars.length; i++) {
    charToInt[chars[i]] = i + 1;
}

const cfg = new GM_configStruct({
    id: "LCFConfig",
    title: `
        <p class = "lcftitle">
            <a href = "https://bit.ly/3Dhqkwl">LCF ${GM_info.script.version}</a>
        </p>
    `,
    events: {
        open: function () {
            makeDraggable(LCFConfig, LCFConfig_header);
            LCFConfig_header.style.cursor = "move";
        },
        save: function () {
            applyFilters();
        }
    },
    fields: {
        filterList: {
            section: ["Filter List", "A list of user accounts to filter"],
            type: "textarea",
            default: "",
            save: true
        },
        filterNew: {
            label: "Filter all new users",
            section: ["Options", "Additional filters and settings"],
            type: "checkbox",
            default: false,
            save: true
        },
        filterImages: {
            label: "Filter all images",
            type: "checkbox",
            default: false,
            save: true
        },
        filterWithML: {
            label: "ML-assisted filter",
            type: "checkbox",
            default: false,
            save: true
        }
    },
    frame: document.body.appendChild(document.createElement("div")),
    css: `
        #LCFConfig {
            font-size: 13px;
			background-color: #f3f6f4;
			position: relative;
            width: 350px;
            margin: 0 auto;
		}
		#LCFConfig textarea {
			font-family: monospace;
			margin-left: auto;
			margin-right: auto;
			-webkit-box-sizing: border-box;
			-moz-box-sizing: border-box;
			box-sizing: border-box;
			width: 100%;
			height: 325px;
			resize: none;
			font-size: 12px;
		}
		#LCFConfig_header p.lcftitle {
			font-size: 20px;
			font-weight: bold;
			margin-bottom: 20px;
            user-select: none;
            padding: 0px;
		}
		#LCFConfig .config_var {
			position: relative;
		}
		#LCFConfig .field_label {
			width: 100%;
			padding-right: 30px;
			box-sizing: border-box;
            user-select: none;
		}
        #LCFConfig .field_label label {
            font-size: 14px;
        }
        #LCFConfig .section_header {
            font-size: 18px;
            font-weight: bold;
            user-select: none;
        }
        #LCFConfig .section_desc {
            font-size: 14px;
            font-style: italic;
            user-select: none;
        }
		#LCFConfig input[type="checkbox"] {
			position: absolute;
			right: 250px;
			top: 50%;
			transform: translateY(-70%);
		}
        #LCFConfig .saveclose_buttons {
            font-size: 14px;
            padding: 5px 10px;
        }
        #LCFConfig .reset {
            user-select: none;
        }
    `
});

function makeDraggable(element, handle) {
    if (!element) {
        return;
    }

    let mdX = 0, mdY = 0, mdeX = 0, mdeY = 0;

    const onMouseMove = (evt) => {
        element.style.left = `${mdeX + evt.clientX - mdX}px`;
        element.style.top = `${mdeY + evt.clientY - mdY}px`;
    };

    const onMouseUp = () => {
        document.removeEventListener("mousemove", onMouseMove);
        document.removeEventListener("mouseup", onMouseUp);
    };

    (handle ?? element).addEventListener("mousedown", function (evt) {
        evt.preventDefault();
        this.style.userSelect = "none";
        mdX = evt.clientX;
        mdY = evt.clientY;
        mdeX = element.offsetLeft;
        mdeY = element.offsetTop;

        document.addEventListener("mousemove", onMouseMove);
        document.addEventListener("mouseup", onMouseUp);
    });
}

function usernameToSequence(username, maxLength) {
    let sequence = [];

    for (let char of username) {
        if (charToInt[char]) {
            sequence.push(charToInt[char]);
        }
    }

    return sequence.concat(Array(maxLength - sequence.length).fill(0));
}

async function fetchRemoteModelVersion() {
    try {
        const response = await fetch(MODEL_VERSION_URL);

        if (!response.ok) {
            throw new Error(`Failed to fetch model version: ${response.statusText}`);
        }

        const version = await response.text();

        return version.trim();
    } catch (error) {
        console.error(`Error fetching remote model version: ${error}`);

        return null;
    }
}

async function initializeTFBackend() {
    if (typeof tf === "undefined") {
        console.error("TensorFlow.js is not loaded");

        return;
    }

    if (MODEL_PROD) {
        await tf.enableProdMode();
    } else {
        await tf.enableDebugMode();
    }

    const isWebGLAvailable = await tf.setBackend("webgl");

    if (isWebGLAvailable) {
        await tf.ready();

        return;
    }

    console.warn("Failed to set the WebGL backend for TensorFlow.js");

    const isWASMAvailable = await tf.setBackend("wasm");

    if (isWASMAvailable) {
        await tf.ready();

        return;
    }

    console.warn("Failed to set the WASM backend for TensorFlow.js");

    const isCPUAvailable = await tf.setBackend("cpu");

    if (isCPUAvailable) {
        await tf.ready();

        return;
    }

    console.warn("Failed to set the CPU backend for TensorFlow.js");
    console.error("No suitable backend available");
}

function applyFilterList(fl) {
    if (fl.length === 0) {
        return;
    }

    const regexPatterns = fl.map(s => new RegExp(`\\b${s.replace(/\*/g, ".*").replace(/\+/g, ".+")}\\b`));
    const rows = Array.from(document.querySelectorAll("tr[valign='top']"));
    const rowsToRemove = [];

    for (let tr of rows) {
        const href = tr?.querySelector("td:nth-child(2) span.ljuser a")?.getAttribute("href") ?? "";

        for (let pattern of regexPatterns) {
            if (pattern.test(href)) {
                rowsToRemove.push(tr);
                break;
            }
        }
    }

    for (let row of rowsToRemove) {
        row.parentNode?.removeChild(row);
    }
}

function applySpamFilter() {
    let filterList = cfg.get("filterList");

    if (typeof filterList !== "string") {
        console.error("Unexpected filter list format");

        return;
    }

    filterList = filterList.split("\n").map(e => e.trim()).filter(e => e.length > 0);
    applyFilterList(filterList);
}

function applyNewUsersFilter() {
    fetch("http://klab.lv/stats.bml")
    .then((res) => {
        if (!res.ok) {
            throw new Error(`Bad network response: ${res.statusText}`);
        }

        return res.text();
    })
    .then((data) => {
        try {
            const dom = new DOMParser().parseFromString(data, "text/html");
            const filterList = Array.from(
                dom.querySelectorAll("ul:nth-of-type(5) a")
            ).map((a) => {
                const match = /([^\/]+)\/$/.exec(a.getAttribute("href"));

                if (!match) {
                    throw new Error("Unexpected URL format");
                }

                return match[1];
            });

            applyFilterList(filterList);
        } catch (parseError) {
            console.error(`Error while parsing or processing the data: ${parseError}`);
        }
    })
    .catch((fetchError) => {
        console.error(`Error in fetch operation: ${fetchError}`);
    });
}

function applyImagesFilter() {
    const images = document.querySelectorAll("img");

    if (images.length === 0) {
        return;
    }

    const imagesToHide = [];

    images.forEach((img) => {
        imagesToHide.push(img);
    });

    imagesToHide.forEach((img) => {
        img.style.display = "none";
    });
}

async function applyMLFilter() {
    try {
        if (!isTFBackendInitialized) {
            await initializeTFBackend();
            isTFBackendInitialized = true;
        }

        const localVersion = localStorage.getItem("modelVersion");
        const remoteVersion = await fetchRemoteModelVersion();

        if (!localStorage[`tensorflowjs_models/${MODEL_NAME}/model_topology`] || (remoteVersion && (!localVersion || remoteVersion > localVersion))) {
            model = await tf.loadLayersModel(MODEL_URL);
            await model.save(`localstorage://${MODEL_NAME}`);
            localStorage.setItem("modelVersion", remoteVersion);
        } else if (!model) {
            model = await tf.loadLayersModel(`localstorage://${MODEL_NAME}`);
        }

        const response = await fetch("http://klab.lv/stats/latest.bml");

        if (!response.ok) {
            throw new Error(`Bad network response: ${response.statusText}`);
        }

        const data = await response.text();
        const maxLength = 16;
        const regex = /<span class='ljuser' style='white-space: nowrap;'>.*?<b>(.*?)<\/b><\/a><\/span>/g;
        const usernames = [];
        let match;

        while ((match = regex.exec(data)) !== null) {
            usernames.push(match[1]);
        }

        const usernameSequences = usernames.map(username => usernameToSequence(username, maxLength));

        tf.tidy(() => {
            const inputTensor = tf.tensor(usernameSequences);
            const outputTensor = model.predict(inputTensor);
            outputTensor.data().then(predictions => {
                const filterList = usernames.filter((username, idx) => predictions[idx] > 0.5);
                applyFilterList(filterList);
            });
        });
    } catch (error) {
        console.error(`Error in ML filter: ${error}`);
    }
}

function applyFilters() {
    applySpamFilter();
    cfg.get("filterNew") && applyNewUsersFilter();
    cfg.get("filterImages") && applyImagesFilter();
    cfg.get("filterWithML") && applyMLFilter();
}

function openConfig() {
    cfg.open();
    LCFConfig.style = `
        height: 75%;
        max-height: 620px;
        top: calc(50% - 350px);
        width: 400px;
        left: calc(50% - 150px);
        border: 1px solid #000000;
        border-radius: 5px;
        margin: 0px;
        opacity: 1.0;
        overflow: auto;
        padding: 10px;
        position: fixed;
        z-index: 65536;
        display: block;
        right: auto;
        bottom: auto;
    `;
}

(function () {
    GM_registerMenuCommand("Settings", openConfig);
    applyFilters();
})();