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Refactor message processing

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Jordan Wages 2025-07-08 19:45:57 -05:00
commit 1b7fa3d5ee
1 changed files with 67 additions and 66 deletions
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133
background.js
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@ -169,10 +169,75 @@ function buildEmailText(full) {
const headers = Object.entries(full.headers || {})
.map(([k, v]) => `${k}: ${v.join(' ')}`)
.join('\n');
const attachInfo = `Attachments: ${attachments.length}` + (attachments.length ? "\n" + attachments.map(a => ` - ${a}`).join('\n') : "");
const attachInfo = `Attachments: ${attachments.length}` +
(attachments.length ? "\n" + attachments.map(a => ` - ${a}`).join('\n') : "");
const combined = `${headers}\n${attachInfo}\n\n${bodyParts.join('\n')}`.trim();
return sanitizeString(combined);
}
function updateTimingStats(elapsed) {
const t = timingStats;
t.count += 1;
t.total += elapsed;
t.last = elapsed;
const delta = elapsed - t.mean;
t.mean += delta / t.count;
t.m2 += delta * (elapsed - t.mean);
}
async function processMessage(id) {
processing = true;
currentStart = Date.now();
queuedCount--;
updateActionIcon();
try {
const full = await messenger.messages.getFull(id);
const text = buildEmailText(full);
let currentTags = [];
try {
const hdr = await messenger.messages.get(id);
currentTags = Array.isArray(hdr.tags) ? [...hdr.tags] : [];
} catch (e) {
currentTags = [];
}
for (const rule of aiRules) {
const cacheKey = await AiClassifier.buildCacheKey(id, rule.criterion);
const matched = await AiClassifier.classifyText(text, rule.criterion, cacheKey);
if (matched) {
for (const act of (rule.actions || [])) {
if (act.type === 'tag' && act.tagKey) {
if (!currentTags.includes(act.tagKey)) {
currentTags.push(act.tagKey);
await messenger.messages.update(id, { tags: currentTags });
}
} else if (act.type === 'move' && act.folder) {
await messenger.messages.move([id], act.folder);
} else if (act.type === 'junk') {
await messenger.messages.update(id, { junk: !!act.junk });
}
}
if (rule.stopProcessing) {
break;
}
}
}
processing = false;
const elapsed = Date.now() - currentStart;
currentStart = 0;
updateTimingStats(elapsed);
await storage.local.set({ classifyStats: timingStats });
showTransientIcon(ICONS.circle);
} catch (e) {
processing = false;
const elapsed = Date.now() - currentStart;
currentStart = 0;
updateTimingStats(elapsed);
await storage.local.set({ classifyStats: timingStats });
logger.aiLog("failed to apply AI rules", { level: 'error' }, e);
showTransientIcon(ICONS.average);
}
}
async function applyAiRules(idsInput) {
const ids = Array.isArray(idsInput) ? idsInput : [idsInput];
if (!ids.length) return queue;
@ -186,71 +251,7 @@ async function applyAiRules(idsInput) {
const id = msg?.id ?? msg;
queuedCount++;
updateActionIcon();
queue = queue.then(async () => {
processing = true;
currentStart = Date.now();
queuedCount--;
updateActionIcon();
try {
const full = await messenger.messages.getFull(id);
const text = buildEmailText(full);
let currentTags = [];
try {
const hdr = await messenger.messages.get(id);
currentTags = Array.isArray(hdr.tags) ? [...hdr.tags] : [];
} catch (e) {
currentTags = [];
}
for (const rule of aiRules) {
const cacheKey = await AiClassifier.buildCacheKey(id, rule.criterion);
const matched = await AiClassifier.classifyText(text, rule.criterion, cacheKey);
if (matched) {
for (const act of (rule.actions || [])) {
if (act.type === 'tag' && act.tagKey) {
if (!currentTags.includes(act.tagKey)) {
currentTags.push(act.tagKey);
await messenger.messages.update(id, { tags: currentTags });
}
} else if (act.type === 'move' && act.folder) {
await messenger.messages.move([id], act.folder);
} else if (act.type === 'junk') {
await messenger.messages.update(id, { junk: !!act.junk });
}
}
if (rule.stopProcessing) {
break;
}
}
}
processing = false;
const elapsed = Date.now() - currentStart;
currentStart = 0;
const t = timingStats;
t.count += 1;
t.total += elapsed;
t.last = elapsed;
const delta = elapsed - t.mean;
t.mean += delta / t.count;
t.m2 += delta * (elapsed - t.mean);
await storage.local.set({ classifyStats: t });
showTransientIcon(ICONS.circle);
} catch (e) {
processing = false;
const elapsed = Date.now() - currentStart;
currentStart = 0;
const t = timingStats;
t.count += 1;
t.total += elapsed;
t.last = elapsed;
const delta = elapsed - t.mean;
t.mean += delta / t.count;
t.m2 += delta * (elapsed - t.mean);
await storage.local.set({ classifyStats: t });
logger.aiLog("failed to apply AI rules", { level: 'error' }, e);
showTransientIcon(ICONS.average);
}
});
queue = queue.then(() => processMessage(id));
}
return queue;