Convert AiClassifier to ES module
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5 changed files with 69 additions and 77 deletions
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@ -1,260 +0,0 @@
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"use strict";
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var { Services } = globalThis || ChromeUtils.importESModule("resource://gre/modules/Services.sys.mjs");
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var { NetUtil } = ChromeUtils.importESModule("resource://gre/modules/NetUtil.sys.mjs");
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var { FileUtils } = ChromeUtils.importESModule("resource://gre/modules/FileUtils.sys.mjs");
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var { aiLog, setDebug } = ChromeUtils.import("resource://aifilter/modules/logger.jsm");
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var EXPORTED_SYMBOLS = ["AiClassifier"];
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const SYSTEM_PREFIX = `You are an email-classification assistant.
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Read the email below and the classification criterion provided by the user.
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`;
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const DEFAULT_CUSTOM_SYSTEM_PROMPT = "Determine whether the email satisfies the user's criterion.";
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const SYSTEM_SUFFIX = `
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Return ONLY a JSON object on a single line of the form:
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{"match": true} - if the email satisfies the criterion
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{"match": false} - otherwise
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Do not add any other keys, text, or formatting.`;
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let gEndpoint = "http://127.0.0.1:5000/v1/classify";
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let gTemplateName = "openai";
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let gCustomTemplate = "";
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let gCustomSystemPrompt = DEFAULT_CUSTOM_SYSTEM_PROMPT;
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let gTemplateText = "";
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let gAiParams = {
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max_tokens: 4096,
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temperature: 0.6,
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top_p: 0.95,
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seed: -1,
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repetition_penalty: 1.0,
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top_k: 20,
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min_p: 0,
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presence_penalty: 0,
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frequency_penalty: 0,
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typical_p: 1,
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tfs: 1,
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};
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let gCache = new Map();
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let gCacheLoaded = false;
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let gCacheFile;
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function ensureCacheFile() {
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if (!gCacheFile) {
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gCacheFile = Services.dirsvc.get("ProfD", Ci.nsIFile);
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gCacheFile.append("aifilter_cache.json");
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}
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}
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function loadCache() {
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if (gCacheLoaded) {
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return;
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}
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ensureCacheFile();
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aiLog(`[AiClassifier] Loading cache from ${gCacheFile.path}`, {debug: true});
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try {
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if (gCacheFile.exists()) {
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let stream = Cc["@mozilla.org/network/file-input-stream;1"].createInstance(Ci.nsIFileInputStream);
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stream.init(gCacheFile, -1, 0, 0);
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let data = NetUtil.readInputStreamToString(stream, stream.available());
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stream.close();
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aiLog(`[AiClassifier] Cache file contents: ${data}`, {debug: true});
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let obj = JSON.parse(data);
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for (let [k, v] of Object.entries(obj)) {
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aiLog(`[AiClassifier] ⮡ Loaded entry '${k}' → ${v}`, {debug: true});
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gCache.set(k, v);
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}
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aiLog(`[AiClassifier] Loaded ${gCache.size} cache entries`, {debug: true});
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} else {
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aiLog(`[AiClassifier] Cache file does not exist`, {debug: true});
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}
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} catch (e) {
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aiLog(`Failed to load cache`, {level: 'error'}, e);
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}
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gCacheLoaded = true;
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}
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function saveCache(updatedKey, updatedValue) {
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ensureCacheFile();
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aiLog(`[AiClassifier] Saving cache to ${gCacheFile.path}`, {debug: true});
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if (typeof updatedKey !== "undefined") {
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aiLog(`[AiClassifier] ⮡ Persisting entry '${updatedKey}' → ${updatedValue}`, {debug: true});
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}
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try {
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let obj = Object.fromEntries(gCache);
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let data = JSON.stringify(obj);
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let stream = Cc["@mozilla.org/network/file-output-stream;1"].createInstance(Ci.nsIFileOutputStream);
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stream.init(gCacheFile,
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FileUtils.MODE_WRONLY | FileUtils.MODE_CREATE | FileUtils.MODE_TRUNCATE,
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FileUtils.PERMS_FILE,
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0);
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stream.write(data, data.length);
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stream.close();
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} catch (e) {
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aiLog(`Failed to save cache`, {level: 'error'}, e);
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}
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}
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function loadTemplate(name) {
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try {
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let url = `resource://aifilter/prompt_templates/${name}.txt`;
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let xhr = new XMLHttpRequest();
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xhr.open("GET", url, false);
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xhr.overrideMimeType("text/plain");
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xhr.send();
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if (xhr.status === 0 || xhr.status === 200) {
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return xhr.responseText;
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}
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} catch (e) {
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aiLog(`Failed to load template '${name}':`, {level: 'error'}, e);
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}
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return "";
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}
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function setConfig(config = {}) {
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if (config.endpoint) {
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gEndpoint = config.endpoint;
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}
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if (config.templateName) {
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gTemplateName = config.templateName;
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}
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if (typeof config.customTemplate === "string") {
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gCustomTemplate = config.customTemplate;
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}
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if (typeof config.customSystemPrompt === "string") {
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gCustomSystemPrompt = config.customSystemPrompt;
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}
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if (config.aiParams && typeof config.aiParams === "object") {
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for (let [k, v] of Object.entries(config.aiParams)) {
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if (k in gAiParams && typeof v !== "undefined") {
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gAiParams[k] = v;
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}
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}
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}
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if (typeof config.debugLogging === "boolean") {
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setDebug(config.debugLogging);
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}
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gTemplateText = gTemplateName === "custom" ? gCustomTemplate : loadTemplate(gTemplateName);
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aiLog(`[AiClassifier] Endpoint set to ${gEndpoint}`, {debug: true});
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aiLog(`[AiClassifier] Template set to ${gTemplateName}`, {debug: true});
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}
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function buildSystemPrompt() {
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return SYSTEM_PREFIX + (gCustomSystemPrompt || DEFAULT_CUSTOM_SYSTEM_PROMPT) + SYSTEM_SUFFIX;
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}
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function buildPrompt(body, criterion) {
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aiLog(`[AiClassifier] Building prompt with criterion: "${criterion}"`, {debug: true});
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const data = {
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system: buildSystemPrompt(),
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email: body,
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query: criterion,
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};
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let template = gTemplateText || loadTemplate(gTemplateName);
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return template.replace(/{{\s*(\w+)\s*}}/g, (m, key) => data[key] || "");
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}
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function getCachedResult(cacheKey) {
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loadCache();
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if (cacheKey && gCache.has(cacheKey)) {
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aiLog(`[AiClassifier] Cache hit for key: ${cacheKey}`, {debug: true});
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return gCache.get(cacheKey);
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}
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return null;
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}
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function buildPayload(text, criterion) {
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let payloadObj = Object.assign({
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prompt: buildPrompt(text, criterion)
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}, gAiParams);
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return JSON.stringify(payloadObj);
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}
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function parseMatch(result) {
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const rawText = result.choices?.[0]?.text || "";
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const thinkText = rawText.match(/<think>[\s\S]*?<\/think>/gi)?.join('') || '';
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aiLog('[AiClassifier] ⮡ Reasoning:', {debug: true}, thinkText);
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const cleanedText = rawText.replace(/<think>[\s\S]*?<\/think>/gi, "").trim();
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aiLog('[AiClassifier] ⮡ Cleaned Response Text:', {debug: true}, cleanedText);
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const obj = JSON.parse(cleanedText);
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return obj.matched === true || obj.match === true;
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}
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function cacheResult(cacheKey, matched) {
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if (cacheKey) {
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aiLog(`[AiClassifier] Caching entry '${cacheKey}' → ${matched}`, {debug: true});
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gCache.set(cacheKey, matched);
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saveCache(cacheKey, matched);
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}
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}
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function classifyTextSync(text, criterion, cacheKey = null) {
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const cached = getCachedResult(cacheKey);
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if (cached !== null) {
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return cached;
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}
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const payload = buildPayload(text, criterion);
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aiLog(`[AiClassifier] Sending classification request to ${gEndpoint}`, {debug: true});
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let matched = false;
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try {
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let xhr = new XMLHttpRequest();
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xhr.open("POST", gEndpoint, false);
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xhr.setRequestHeader("Content-Type", "application/json");
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xhr.send(payload);
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if (xhr.status >= 200 && xhr.status < 300) {
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const result = JSON.parse(xhr.responseText);
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aiLog(`[AiClassifier] Received response:`, {debug: true}, result);
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matched = parseMatch(result);
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cacheResult(cacheKey, matched);
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} else {
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aiLog(`HTTP status ${xhr.status}`, {level: 'warn'});
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}
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} catch (e) {
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aiLog(`HTTP request failed`, {level: 'error'}, e);
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}
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return matched;
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}
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async function classifyText(text, criterion, cacheKey = null) {
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const cached = getCachedResult(cacheKey);
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if (cached !== null) {
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return cached;
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}
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const payload = buildPayload(text, criterion);
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aiLog(`[AiClassifier] Sending classification request to ${gEndpoint}`, {debug: true});
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try {
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const response = await fetch(gEndpoint, {
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method: "POST",
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headers: { "Content-Type": "application/json" },
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body: payload,
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});
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if (!response.ok) {
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aiLog(`HTTP status ${response.status}`, {level: 'warn'});
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return false;
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}
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const result = await response.json();
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aiLog(`[AiClassifier] Received response:`, {debug: true}, result);
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const matched = parseMatch(result);
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cacheResult(cacheKey, matched);
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return matched;
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} catch (e) {
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aiLog(`HTTP request failed`, {level: 'error'}, e);
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return false;
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}
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}
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var AiClassifier = { classifyText, classifyTextSync, setConfig };
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