update: insertion of snapshot schedule

.zed/settings.json

@@ -3,33 +3,33 @@
 // For a full list of overridable settings, and general information on folder-specific settings,
 // see the documentation: https://zed.dev/docs/configuring-zed#settings-files
 {
-    "lsp": {
+	"lsp": {
-        "deno": {
+		"deno": {
-            "settings": {
+			"settings": {
-                "deno": {
+				"deno": {
-                    "enable": true
+					"enable": true
-                }
+				}
-            }
+			}
-        }
+		}
-    },
+	},
-    "languages": {
+	"languages": {
-        "TypeScript": {
+		"TypeScript": {
-            "language_servers": [
+			"language_servers": [
-                "deno",
+				"deno",
-                "!typescript-language-server",
+				"!typescript-language-server",
-                "!vtsls",
+				"!vtsls",
-                "!eslint"
+				"!eslint"
-            ],
+			],
-            "formatter": "language_server"
+			"formatter": "language_server"
-        },
+		},
-        "TSX": {
+		"TSX": {
-            "language_servers": [
+			"language_servers": [
-                "deno",
+				"deno",
-                "!typescript-language-server",
+				"!typescript-language-server",
-                "!vtsls",
+				"!vtsls",
-                "!eslint"
+				"!eslint"
-            ],
+			],
-            "formatter": "language_server"
+			"formatter": "language_server"
-        }
+		}
-    }
+	}
 }

lib/db/allData.ts

@@ -3,7 +3,10 @@ import { AllDataType, BiliUserType } from "lib/db/schema.d.ts";
 import Akari from "lib/ml/akari.ts";
 
 export async function videoExistsInAllData(client: Client, aid: number) {
-	return await client.queryObject<{ exists: boolean }>(`SELECT EXISTS(SELECT 1 FROM bilibili_metadata WHERE aid = $1)`, [aid])
+	return await client.queryObject<{ exists: boolean }>(
+		`SELECT EXISTS(SELECT 1 FROM bilibili_metadata WHERE aid = $1)`,
+		[aid],
+	)
 		.then((result) => result.rows[0].exists);
 }
 

lib/db/schema.d.ts

@@ -31,3 +31,13 @@ export interface VideoSnapshotType {
 	aid: bigint;
 	replies: number;
 }
+
+export interface SnapshotScheduleType {
+	id: number;
+	aid: number;
+	type?: string;
+	created_at: string;
+	started_at?: string;
+	finished_at?: string;
+	status: string;
+}

lib/db/snapshotSchedule.ts

@@ -1,4 +1,7 @@
+import { DAY, MINUTE } from "$std/datetime/constants.ts";
 import { Client } from "https://deno.land/x/postgres@v0.19.3/mod.ts";
+import { formatTimestampToPsql } from "lib/utils/formatTimestampToPostgre.ts";
+import { SnapshotScheduleType } from "./schema.d.ts";
 
 /*
     Returns true if the specified `aid` has at least one record with "pending" or "processing" status.
@@ -22,11 +25,12 @@ export async function findClosestSnapshot(
 	targetTime: Date,
 ): Promise<Snapshot | null> {
 	const query = `
-        SELECT created_at, views FROM video_snapshot
+        SELECT created_at, views
+        FROM video_snapshot
         WHERE aid = $1
-        ORDER BY ABS(EXTRACT(EPOCH FROM (created_at - $2::timestamptz))) ASC
+        ORDER BY ABS(EXTRACT(EPOCH FROM (created_at - $2::timestamptz)))
         LIMIT 1
-    `;
+	`;
 	const result = await client.queryObject<{ created_at: string; views: number }>(
 		query,
 		[aid, targetTime.toISOString()],
@@ -39,7 +43,7 @@ export async function findClosestSnapshot(
 	};
 }
 
-export async function getLatestSnapshot(client: Client, aid: number): Promise<Snapshot | null>{
+export async function getLatestSnapshot(client: Client, aid: number): Promise<Snapshot | null> {
 	const res = await client.queryObject<{ created_at: string; views: number }>(
 		`SELECT created_at, views FROM video_snapshot WHERE aid = $1 ORDER BY created_at DESC LIMIT 1`,
 		[aid],
@@ -49,5 +53,112 @@ export async function getLatestSnapshot(client: Client, aid: number): Promise<Sn
 	return {
 		created_at: new Date(row.created_at).getTime(),
 		views: row.views,
-	}
+	};
+}
+
+/*
+ * Returns the number of snapshot schedules within the specified range.
+ * @param client The database client.
+ * @param start The start time of the range. (Timestamp in milliseconds)
+ * @param end The end time of the range. (Timestamp in milliseconds)
+ */
+export async function getSnapshotScheduleCountWithinRange(client: Client, start: number, end: number) {
+	const startTimeString = formatTimestampToPsql(start);
+	const endTimeString = formatTimestampToPsql(end);
+	const query = `
+		SELECT COUNT(*) FROM snapshot_schedule
+		WHERE started_at BETWEEN $1 AND $2
+		AND status = 'pending'
+	`;
+	const res = await client.queryObject<{ count: number }>(query, [startTimeString, endTimeString]);
+	return res.rows[0].count;
+}
+
+/*
+ * Creates a new snapshot schedule record.
+ * @param client The database client.
+ * @param aid The aid of the video.
+ * @param targetTime Scheduled time for snapshot. (Timestamp in milliseconds)
+ */
+export async function scheduleSnapshot(client: Client, aid: number, type: string, targetTime: number) {
+	const ajustedTime = await adjustSnapshotTime(client, new Date(targetTime));
+	return client.queryObject(
+		`INSERT INTO snapshot_schedule (aid, type, started_at) VALUES ($1, $2, $3)`,
+		[aid, type, ajustedTime.toISOString()],
+	);
+}
+
+/**
+ * Adjust the trigger time of the snapshot to ensure it does not exceed the frequency limit
+ * @param client PostgreSQL client
+ * @param expectedStartTime The expected snapshot time
+ * @returns The adjusted actual snapshot time
+ */
+export async function adjustSnapshotTime(
+	client: Client,
+	expectedStartTime: Date,
+): Promise<Date> {
+	const findWindowQuery = `
+        WITH windows AS (
+            SELECT generate_series(
+				   $1::timestamp,  -- Start time: current time truncated to the nearest 5-minute window
+				   $2::timestamp,  -- End time: 24 hours after the target time window starts
+				   INTERVAL '5 MINUTES'
+		   ) AS window_start
+        )
+        SELECT w.window_start
+        FROM windows w
+        	LEFT JOIN snapshot_schedule s ON s.started_at >= w.window_start
+			AND s.started_at < w.window_start + INTERVAL '5 MINUTES'
+			AND s.status = 'pending'
+        GROUP BY w.window_start
+        HAVING COUNT(s.*) < 2000
+        ORDER BY w.window_start
+        LIMIT 1;
+	`;
+	for (let i = 0; i < 7; i++) {
+		const now = new Date(new Date().getTime() + 5 * MINUTE);
+		const nowTruncated = truncateTo5MinInterval(now);
+		const currentWindowStart = truncateTo5MinInterval(expectedStartTime);
+		const end = new Date(currentWindowStart.getTime() + 1 * DAY);
+
+		const windowResult = await client.queryObject<{ window_start: Date }>(
+			findWindowQuery,
+			[nowTruncated, end],
+		);
+
+		const windowStart = windowResult.rows[0]?.window_start;
+		if (!windowStart) {
+			continue;
+		}
+
+		return windowStart;
+	}
+	return expectedStartTime;
+}
+
+/**
+ * Truncate the timestamp to the nearest 5-minute interval
+ * @param timestamp The timestamp
+ * @returns The truncated time
+ */
+function truncateTo5MinInterval(timestamp: Date): Date {
+	const minutes = timestamp.getMinutes() - (timestamp.getMinutes() % 5);
+	return new Date(
+		timestamp.getFullYear(),
+		timestamp.getMonth(),
+		timestamp.getDate(),
+		timestamp.getHours(),
+		minutes,
+		0,
+		0,
+	);
+}
+
+export async function getSnapshotsInNextSecond(client: Client) {
+	const res = await client.queryObject<SnapshotScheduleType>(
+		`SELECT * FROM cvsa.public.snapshot_schedule WHERE started_at <= NOW() + INTERVAL '1 second'`,
+		[],
+	);
+	return res.rows;
 }

lib/ml/benchmark.ts

@@ -1,7 +1,6 @@
 import { AutoTokenizer, PreTrainedTokenizer } from "@huggingface/transformers";
 import * as ort from "onnxruntime";
 
-
 function softmax(logits: Float32Array): number[] {
 	const maxLogit = Math.max(...logits);
 	const exponents = logits.map((logit) => Math.exp(logit - maxLogit));

lib/ml/manager.ts

@@ -21,10 +21,10 @@ export class AIManager {
 		}
 	}
 
-    public getModelSession(key: string): ort.InferenceSession {
+	public getModelSession(key: string): ort.InferenceSession {
-        if (this.sessions[key] === undefined) {
+		if (this.sessions[key] === undefined) {
-            throw new WorkerError(new Error(`Model ${key} not found / not initialized.`), "ml", "fn:getModelSession");
+			throw new WorkerError(new Error(`Model ${key} not found / not initialized.`), "ml", "fn:getModelSession");
-        }
+		}
 		return this.sessions[key];
 	}
 

lib/ml/mantis.ts

@@ -6,19 +6,16 @@ import { WorkerError } from "lib/mq/schema.ts";
 const modelPath = "./model/model.onnx";
 
 class MantisProto extends AIManager {
-
 	constructor() {
 		super();
-        this.models = {
+		this.models = {
-            "predictor": modelPath,
+			"predictor": modelPath,
-        }
+		};
 	}
 
-    public override async init(): Promise<void> {
+	public override async init(): Promise<void> {
-        await super.init();
+		await super.init();
-    }
+	}
-
-    
 }
 
 const Mantis = new MantisProto();

lib/mq/exec/snapshotTick.ts

@@ -1,21 +1,37 @@
 import { Job } from "bullmq";
 import { db } from "lib/db/init.ts";
 import { getVideosNearMilestone } from "lib/db/snapshot.ts";
-import { findClosestSnapshot, getLatestSnapshot, videoHasActiveSchedule } from "lib/db/snapshotSchedule.ts";
+import {
+	findClosestSnapshot,
+	getLatestSnapshot,
+	getSnapshotsInNextSecond,
+	scheduleSnapshot,
+	videoHasActiveSchedule,
+} from "lib/db/snapshotSchedule.ts";
 import { Client } from "https://deno.land/x/postgres@v0.19.3/mod.ts";
 import { HOUR, MINUTE } from "$std/datetime/constants.ts";
+import logger from "lib/log/logger.ts";
+import { SnapshotQueue } from "lib/mq/index.ts";
+
+const priorityMap: { [key: string]: number } = {
+	"milestone": 1,
+};
 
 export const snapshotTickWorker = async (_job: Job) => {
 	const client = await db.connect();
 	try {
-		// TODO: implement
+		const schedules = await getSnapshotsInNextSecond(client);
+		for (const schedule of schedules) {
+			let priority = 3;
+			if (schedule.type && priorityMap[schedule.type])
+				priority = priorityMap[schedule.type];
+			await SnapshotQueue.add("snapshotVideo", { aid: schedule.aid, priority });
+		}
 	} finally {
 		client.release();
 	}
 };
 
-const log = (a: number, b: number = 10) => Math.log(a) / Math.log(b);
-
 export const closetMilestone = (views: number) => {
 	if (views < 100000) return 100000;
 	if (views < 1000000) return 1000000;
@@ -24,6 +40,12 @@ export const closetMilestone = (views: number) => {
 
 const log = (value: number, base: number = 10) => Math.log(value) / Math.log(base);
 
+/*
+ * Returns the minimum ETA in hours for the next snapshot
+ * @param client - Postgres client
+ * @param aid - aid of the video
+ * @returns ETA in hours
+ */
 const getAdjustedShortTermETA = async (client: Client, aid: number) => {
 	const latestSnapshot = await getLatestSnapshot(client, aid);
 	// Immediately dispatch a snapshot if there is no snapshot yet
@@ -61,10 +83,12 @@ export const collectMilestoneSnapshotsWorker = async (_job: Job) => {
 			if (await videoHasActiveSchedule(client, video.aid)) continue;
 			const eta = await getAdjustedShortTermETA(client, video.aid);
 			if (eta > 72) continue;
-			// TODO: dispatch snapshot job
+			const now = Date.now();
+			const targetTime = now + eta * HOUR;
+			await scheduleSnapshot(client, video.aid, "milestone", targetTime);
 		}
-	} catch (_e) {
+	} catch (e) {
-		//
+		logger.error(e as Error, "mq", "fn:collectMilestoneSnapshotsWorker");
 	} finally {
 		client.release();
 	}

lib/mq/scheduler.ts

@@ -288,7 +288,11 @@ class NetScheduler {
 				const fileId = randomUUID();
 				await Deno.writeFile(`./logs/files/${fileId}.stdout`, output.stdout);
 				await Deno.writeFile(`./logs/files/${fileId}.stderr`, output.stderr);
-				logger.log(`Returned non-200 status code. Raw ouput saved to ./logs/files/${fileId}.stdout/stderr`, "net", "fn:alicloudFcRequest")
+				logger.log(
+					`Returned non-200 status code. Raw ouput saved to ./logs/files/${fileId}.stdout/stderr`,
+					"net",
+					"fn:alicloudFcRequest",
+				);
 				throw new NetSchedulerError(
 					`Error proxying ${url} to ali-fc region ${region}, code: ${rawData.statusCode}.`,
 					"ALICLOUD_PROXY_ERR",
@@ -301,7 +305,11 @@ class NetScheduler {
 				const fileId = randomUUID();
 				rawOutput && await Deno.writeFile(`./logs/files/${fileId}.stdout`, rawOutput);
 				rawErr && await Deno.writeFile(`./logs/files/${fileId}.stderr`, rawErr);
-				logger.log(`Error occurred. Raw ouput saved to ./logs/files/${fileId}.stdout/stderr`, "net", "fn:alicloudFcRequest")
+				logger.log(
+					`Error occurred. Raw ouput saved to ./logs/files/${fileId}.stdout/stderr`,
+					"net",
+					"fn:alicloudFcRequest",
+				);
 			}
 			logger.error(e as Error, "net", "fn:alicloudFcRequest");
 			throw new NetSchedulerError(`Unhandled error: Cannot proxy ${url} to ali-fc.`, "ALICLOUD_PROXY_ERR", e);

lib/mq/task/getVideoStats.ts

@@ -3,30 +3,33 @@ import { getVideoInfo } from "lib/net/getVideoInfo.ts";
 
 export async function insertVideoStats(client: Client, aid: number, task: string) {
 	const data = await getVideoInfo(aid, task);
-    const time = new Date().getTime();
+	const time = new Date().getTime();
-    if (typeof data == 'number') {
+	if (typeof data == "number") {
 		return data;
 	}
-    const views = data.stat.view;
+	const views = data.stat.view;
-    const danmakus = data.stat.danmaku;
+	const danmakus = data.stat.danmaku;
-    const replies = data.stat.reply;
+	const replies = data.stat.reply;
-    const likes = data.stat.like;
+	const likes = data.stat.like;
-    const coins = data.stat.coin;
+	const coins = data.stat.coin;
-    const shares = data.stat.share;
+	const shares = data.stat.share;
-    const favorites = data.stat.favorite;
+	const favorites = data.stat.favorite;
-    await client.queryObject(`
+	await client.queryObject(
+		`
         INSERT INTO video_snapshot (aid, views, danmakus, replies, likes, coins, shares, favorites)
         VALUES ($1, $2, $3, $4, $5, $6, $7, $8)
-    `, [aid, views, danmakus, replies, likes, coins, shares, favorites]);
+    `,
-    return {
+		[aid, views, danmakus, replies, likes, coins, shares, favorites],
-        aid,
+	);
-        views,
+	return {
-        danmakus,
+		aid,
-        replies,
+		views,
-        likes,
+		danmakus,
-        coins,
+		replies,
-        shares,
+		likes,
-        favorites,
+		coins,
-        time
+		shares,
-    }
+		favorites,
+		time,
+	};
 }

lib/net/bilibili.d.ts

@@ -26,8 +26,8 @@ interface VideoInfoData {
 		mid: number;
 		name: string;
 		face: string;
-	},
+	};
-	stat: VideoStats,
+	stat: VideoStats;
 }
 
 interface VideoDetailsData {

lib/utils/formatSeconds.ts

@@ -1,6 +1,6 @@
 export const formatSeconds = (seconds: number) => {
 	if (seconds < 60) {
-		return `${(seconds).toFixed(1)}s`;
+		return `${seconds.toFixed(1)}s`;
 	}
 	if (seconds < 3600) {
 		return `${Math.floor(seconds / 60)}m${(seconds % 60).toFixed(1)}s`;

src/worker.ts

@@ -5,7 +5,11 @@ import logger from "lib/log/logger.ts";
 import { lockManager } from "lib/mq/lockManager.ts";
 import { WorkerError } from "lib/mq/schema.ts";
 import { getVideoInfoWorker } from "lib/mq/exec/getLatestVideos.ts";
-import { snapshotTickWorker, collectMilestoneSnapshotsWorker, takeSnapshotForVideoWorker } from "lib/mq/exec/snapshotTick.ts";
+import {
+	collectMilestoneSnapshotsWorker,
+	snapshotTickWorker,
+	takeSnapshotForVideoWorker,
+} from "lib/mq/exec/snapshotTick.ts";
 
 Deno.addSignalListener("SIGINT", async () => {
 	logger.log("SIGINT Received: Shutting down workers...", "mq");
@@ -75,4 +79,4 @@ const snapshotWorker = new Worker(
 snapshotWorker.on("error", (err) => {
 	const e = err as WorkerError;
 	logger.error(e.rawError, e.service, e.codePath);
-})
+});

test/ml/akari.json

@@ -1,22 +1,22 @@
 {
-    "test1": [
+	"test1": [
-        {
+		{
-            "title": "【洛天依】《一花依世界》（2024重调版）|“抬头仰望，夜空多安详”【原创PV付】",
+			"title": "【洛天依】《一花依世界》（2024重调版）|“抬头仰望，夜空多安详”【原创PV付】",
-            "desc": "本家：BV1Vs411H7JH\n作曲：LS\n作词：杏花包子\n调教：鬼面P\n混音：虎皮猫P\n演唱：洛天依\n曲绘：山下鸭鸭窝\n映像：阿妍\n——————————————————————\n本稿为同人二创，非本家重制",
+			"desc": "本家：BV1Vs411H7JH\n作曲：LS\n作词：杏花包子\n调教：鬼面P\n混音：虎皮猫P\n演唱：洛天依\n曲绘：山下鸭鸭窝\n映像：阿妍\n——————————————————————\n本稿为同人二创，非本家重制",
-            "tags": "发现《一花依世界》, Vsinger创作激励计划, 洛天依, VOCALOID CHINA, 翻唱, 原创PV付, ACE虚拟歌姬, 中文VOCALOID, 国风电子, 一花依世界, ACE Studio, Vsinger创作激励计划2024冬季物语",
+			"tags": "发现《一花依世界》, Vsinger创作激励计划, 洛天依, VOCALOID CHINA, 翻唱, 原创PV付, ACE虚拟歌姬, 中文VOCALOID, 国风电子, 一花依世界, ACE Studio, Vsinger创作激励计划2024冬季物语",
-            "label": 2
+			"label": 2
-        },
+		},
-        {
+		{
-            "title": "【鏡音レン】アカシア【VOCALOID Cover】",
+			"title": "【鏡音レン】アカシア【VOCALOID Cover】",
-            "desc": "鏡音リン・レン 13th Anniversary\n\nMusic：BUMP OF CHICKEN https://youtu.be/BoZ0Zwab6Oc\nust：Maplestyle sm37853236\nOff Vocal: https://youtu.be/YMzrUzq1uX0\nSinger：鏡音レン\n\n氷雨ハルカ\nYoutube ：https://t.co/8zuv6g7Acm\nniconico：https://t.co/C6DRfdYAp0\ntwitter ：https://twitter.com/hisame_haruka\n\n転載禁止\nPlease do not reprint without my permission.",
+			"desc": "鏡音リン・レン 13th Anniversary\n\nMusic：BUMP OF CHICKEN https://youtu.be/BoZ0Zwab6Oc\nust：Maplestyle sm37853236\nOff Vocal: https://youtu.be/YMzrUzq1uX0\nSinger：鏡音レン\n\n氷雨ハルカ\nYoutube ：https://t.co/8zuv6g7Acm\nniconico：https://t.co/C6DRfdYAp0\ntwitter ：https://twitter.com/hisame_haruka\n\n転載禁止\nPlease do not reprint without my permission.",
-            "tags": "鏡音レン",
+			"tags": "鏡音レン",
-            "label": 0
+			"label": 0
-        },
+		},
-        {
+		{
-            "title": "【洛天依原创曲】谪星【姆斯塔之谕】",
+			"title": "【洛天依原创曲】谪星【姆斯塔之谕】",
-            "desc": "谪星\n\n策划/世界观：听雨\n作词：听雨\n作曲/编曲：太白\n混音：虎皮猫\n人设：以木\n曲绘：Ar极光\n调校：哈士奇p\n视频：苏卿白",
+			"desc": "谪星\n\n策划/世界观：听雨\n作词：听雨\n作曲/编曲：太白\n混音：虎皮猫\n人设：以木\n曲绘：Ar极光\n调校：哈士奇p\n视频：苏卿白",
-            "tags": "2025虚拟歌手贺岁纪, 洛天依, 原创歌曲, VOCALOID, 虚拟歌手, 原创音乐, 姆斯塔, 中文VOCALOID",
+			"tags": "2025虚拟歌手贺岁纪, 洛天依, 原创歌曲, VOCALOID, 虚拟歌手, 原创音乐, 姆斯塔, 中文VOCALOID",
-            "label": 1
+			"label": 1
-        }
+		}
-    ]
+	]
 }

test/ml/akari.test.ts

@@ -4,43 +4,43 @@ import { join } from "$std/path/join.ts";
 import { SECOND } from "$std/datetime/constants.ts";
 
 Deno.test("Akari AI - normal cases accuracy test", async () => {
-    const path = import.meta.dirname!;
+	const path = import.meta.dirname!;
-    const dataPath = join(path, "akari.json");
+	const dataPath = join(path, "akari.json");
-    const rawData = await Deno.readTextFile(dataPath);
+	const rawData = await Deno.readTextFile(dataPath);
-    const data = JSON.parse(rawData);
+	const data = JSON.parse(rawData);
-    await Akari.init();
+	await Akari.init();
-    for (const testCase of data.test1) {
+	for (const testCase of data.test1) {
-        const result = await Akari.classifyVideo(
+		const result = await Akari.classifyVideo(
-            testCase.title, 
+			testCase.title,
-            testCase.desc,
+			testCase.desc,
-            testCase.tags
+			testCase.tags,
-        );
+		);
-        assertEquals(result, testCase.label);
+		assertEquals(result, testCase.label);
-    }
+	}
 });
 
 Deno.test("Akari AI - performance test", async () => {
-    const path = import.meta.dirname!;
+	const path = import.meta.dirname!;
-    const dataPath = join(path, "akari.json");
+	const dataPath = join(path, "akari.json");
-    const rawData = await Deno.readTextFile(dataPath);
+	const rawData = await Deno.readTextFile(dataPath);
-    const data = JSON.parse(rawData);
+	const data = JSON.parse(rawData);
-    await Akari.init();
+	await Akari.init();
-    const N = 200;
+	const N = 200;
-    const testCase = data.test1[0];
+	const testCase = data.test1[0];
-    const title = testCase.title;
+	const title = testCase.title;
-    const desc = testCase.desc;
+	const desc = testCase.desc;
-    const tags = testCase.tags;
+	const tags = testCase.tags;
-    const time = performance.now();
+	const time = performance.now();
-    for (let i = 0; i < N; i++){
+	for (let i = 0; i < N; i++) {
-        await Akari.classifyVideo(
+		await Akari.classifyVideo(
-            title,
+			title,
-            desc,
+			desc,
-            tags
+			tags,
-        );
+		);
-    }
+	}
-    const end = performance.now();
+	const end = performance.now();
-    const elapsed = (end - time) / SECOND;
+	const elapsed = (end - time) / SECOND;
-    const throughput = N / elapsed;
+	const throughput = N / elapsed;
-    assertGreaterOrEqual(throughput, 100);
+	assertGreaterOrEqual(throughput, 100);
-    console.log(`Akari AI throughput: ${throughput.toFixed(1)} samples / sec`)
+	console.log(`Akari AI throughput: ${throughput.toFixed(1)} samples / sec`);
-});
+});