@aetherz/scraper
Version:
Scraper
527 lines (493 loc) • 15.7 kB
JavaScript
const cheerio = require("cheerio");
const fetch = require("node-fetch");
/**
* SCRAPED BY AETHER
* FORBIDDEN TO REMOVE WM
* Follow For More Scrape
* @link https://kavian.xyz/s/ch
* @class Ai
*/
class Ai {
constructor() {
this.BASE = "https://boredhumans.com";
this.BASE_URL = this.BASE + "/apis/boredagi_api.php";
this.BASE_CDN = this.BASE + "/boredagi_files";
this.BASE_UPLOAD = this.BASE + "/apis/boredagi_upload.php";
this.uid = {};
this.sesh_id = {};
this.tools = {
celebrity_ai: 10,
txt2img: 3,
img_recognition: 6,
txt2speech: 116,
};
this.num = 0;
this.text = {
10: "I want to talk to someone famous.",
3: "Can you generate an image?",
6: "Describe this image for me.",
116: "Connect me to Text-To-Speech (TTS) Tool",
};
}
// ? FUNCTION
#getUid() {
this.uid[this.num] =
Date.now().toString(36) + Math.random().toString(36).slice(2);
}
async #getSeshId() {
await this.#getUid();
const res = await fetch(this.BASE_URL, {
method: "POST",
headers: {
"User-Agent": navigator.userAgent,
},
body: new URLSearchParams({
prompt: encodeURIComponent(this.text[this.num]),
uid: this.uid[this.num],
sesh_id: "None",
get_tool: false,
tool_num: this.num,
}),
}).then((v) => v.json());
if (res.status !== "success") return (this.sesh_id[this.num] = "none");
return (this.sesh_id[this.num] = res.sesh_id);
}
// ? AI
async celebrityAi(prompt) {
return new Promise(async (resolve, reject) => {
try {
this.num = this.tools.celebrity_ai;
if (!this.sesh_id[this.num]) await this.#getSeshId();
const data = new URLSearchParams({
prompt: encodeURIComponent(prompt),
uid: this.uid[this.num],
sesh_id: this.sesh_id[this.num],
get_tool: false,
tool_num: this.num,
});
const res = await fetch(this.BASE_URL, {
method: "POST",
headers: {
"User-Agent": navigator.userAgent,
},
body: data,
}).then((v) => v.json());
if (res.status !== "success")
return (async () => {
await this.#getSeshId();
await this.celebrityAi(prompt);
})();
return resolve(res.output);
} catch (e) {
reject(e);
}
});
}
async txt2img(prompt) {
return new Promise(async (resolve, reject) => {
try {
this.num = this.tools.txt2img;
if (!this.sesh_id[this.num]) await this.#getSeshId();
const data = {
prompt: encodeURIComponent(prompt),
uid: this.uid[this.num],
sesh_id: this.sesh_id[this.num],
get_tool: false,
tool_num: this.num,
};
const res = await fetch(this.BASE_URL, {
method: "POST",
headers: {
"User-Agent": navigator.userAgent,
},
body: new URLSearchParams(data),
})
.then((v) => v.json())
.then((v) =>
(async () => {
data.prompt = "yes";
return await fetch(this.BASE_URL, {
method: "POST",
headers: {
"User-Agent": navigator.userAgent,
},
body: new URLSearchParams(data),
}).then((v) => v.json());
})()
);
if (res.status !== "success")
return (async () => {
await this.#getSeshId();
await this.txt2img(prompt);
})();
const $ = cheerio.load(res.output);
await this.#getSeshId();
return resolve($("img").attr("src"));
} catch (e) {
reject(e);
}
});
}
async imageRecognition(url, prompt) {
return new Promise(async (resolve, reject) => {
try {
this.num = this.tools.img_recognition;
if (!this.sesh_id[this.num]) await this.#getSeshId();
const data = new URLSearchParams({
prompt: encodeURIComponent(url),
uid: this.uid[this.num],
sesh_id: this.sesh_id[this.num],
get_tool: false,
tool_num: this.num,
});
fetch(this.BASE_URL, {
method: "POST",
headers: {
"User-Agent": navigator.userAgent,
},
body: data,
})
.then((v) => v.json())
.then((v) =>
(async () => {
data.set("prompt", encodeURIComponent(prompt));
fetch(this.BASE_URL, {
method: "POST",
headers: {
"User-Agent": navigator.userAgent,
},
body: data,
})
.then((v) => v.json())
.then((v) => async () => {
await this.#getSeshId();
resolve(v.output);
});
})()
);
} catch (e) {
reject(e);
}
});
}
async txt2speech(prompt) {
return new Promise(async (resolve, reject) => {
try {
this.num = this.tools.txt2speech;
if (!this.sesh_id[this.num]) await this.#getSeshId();
const data = new URLSearchParams({
prompt: encodeURIComponent(prompt),
uid: this.uid[this.num],
sesh_id: this.sesh_id[this.num],
get_tool: false,
tool_num: this.num,
});
fetch(this.BASE_URL, {
method: "POST",
headers: {
"User-Agent": navigator.userAgent,
},
body: data,
})
.then((v) => v.json())
.then((v) =>
(async () => {
await this.#getSeshId();
return resolve(v.output);
})()
);
} catch (e) {
reject(e);
}
});
}
}
/**
* Scraped By AETHER
* Protected By MIT LICENSE
* Whoever caught removing wm will be sued
* @description Any Request? Contact me : aetherscode@gmail.com
* @author AETHER 2024
* @copyright https://aetherz.xyz
*/
async function stableDiff(prompt, negative = "") {
return new Promise(async (resolve, reject) => {
try {
if (!prompt) return reject("Enter Prompt!");
const res = await fetch(
"https://requesteracessibili.joaovitorkas13.workers.dev",
{
method: "POST",
headers: {
authority: "requesteracessibili.joaovitorkas13.workers.dev",
"content-type": "application/json",
origin: "https://just4demo24.blogspot.com",
referer: "https://just4demo24.blogspot.com/",
"user-agent":
"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/126.0.0.0 Safari/537.36",
},
body: JSON.stringify({
prompt: prompt,
negative_prompt: negative,
sync_mode: 1,
}),
}
).then((v) => v.json());
return resolve(res);
} catch (e) {
reject(e);
}
});
}
/**
* Scraped By AETHER
* Protected By MIT LICENSE
* Whoever caught removing wm will be sued
* @param {{
* prompt : String,
* negative : String,
* style : "(none)"|"Cinematic"|"Photographic"|"Anime"|"Manga"|"Digital Art"|"Pixel art"|"Fantasy art"|"Neonpunk"|"3D Model",
* sampler : "DDIM"|"Euler a"|"Euler"|"DPM++ 2M Karras"|"DPM++ 2M SDE Karras"|"DPM++ SDE Karras",
* quality : "(none)"|"Light"|"Standard"|"Heavy",
* width : Number,
* height : Number,
* ratio : "Custom"|"640 x 1536"|"832 x 1216"|"1024 x 1024"|"1152 x 896"|"1344 x 768"|"768 x 1344"|"896 x 1152"|"1216 x 832"|"1536 x 640"
* }} [options={}]
* @description Any Request? Contact me : aetherscode@gmail.com
* @author AETHER 2024
* @copyright https://aetherz.xyz
*/
async function animagine(options = {}) {
return new Promise(async (resolve, reject) => {
try {
let {
prompt = "Cute Cat",
negative = "Not Real",
style = "Anime",
sampler = "Euler a",
ratio = "896 x 1152",
quality = "Standard",
width = "1024",
height = "1024",
} = options;
const BASE_URL = "https://linaqruf-animagine-xl.hf.space";
const session_hash = Math.random().toString(36).substring(2);
// ? Checker
if (
!/\(None\)|Cinematic|Photographic|Anime|Manga|Digital Art|Pixel art|Fantasy art|Neonpunk|3D Model/.test(
style
)
)
style = "Anime";
if (
!/DDIM|Euler a|Euler|DPM\+\+ 2M Karras|DPM\+\+ 2M SDE Karras|DPM\+\+ SDE Karras/.test(
sampler
)
)
sampler = "Euler a";
if (!/\(none\)|Light|Standard|Heavy/.test(quality)) quality = "Heavy";
if (
!/Custom|640 x 1536|832 x 1216|1024 x 1024|1152 x 896|1344 x 768|768 x 1344|896 x 1152|1216 x 832|1536 x 640/.test(
ratio
)
)
ratio = "896 x 1152";
if (quality === "Custom")
async () => {
if (!width || isNaN(width) || +width > 2048)
return reject("Enter Valid Image Width Below 2048");
if (!height || isNaN(height) || +height > 2048)
return reject("Enter Valid Image Height Below 2048");
};
// ? Headers
const headers = {
origin: BASE_URL,
referer: BASE_URL + "/?",
"user-agent":
"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/126.0.0.0 Safari/537.36",
"content-type": "application/json",
};
// ? Token
const { data: token } = await fetch(BASE_URL + "/run/predict", {
method: "POST",
headers,
body: JSON.stringify({
data: [0, true],
event_data: null,
fn_index: 4,
session_hash,
trigger_id: 6,
}),
}).then((v) => v.json());
// ? Join
await fetch(BASE_URL + "/queue/join?", {
method: "POST",
headers,
body: JSON.stringify({
data: [
prompt,
negative,
token[0],
width,
height,
7,
28, // ? Step
sampler, // ? Sampler
ratio, // ? Aspect ratio
style, // ? Style
quality, // ? Quality
false,
0.55,
1.5,
true,
],
event_data: null,
fn_index: 5,
session_hash,
trigger_id: 7,
}),
}).then((v) => v.json());
// ? Generate Images
const stream = await fetch(
BASE_URL + "/queue/data?" + new URLSearchParams({ session_hash })
).then((v) => v.body);
// ? Handle Stream
stream.on("data", (v) => {
const data = JSON.parse(v.toString().split("data: ")[1]);
if (data.msg !== "process_completed") return;
if (!data.success) return reject("Image Generation Failed!");
return resolve(data.output.data[0]);
});
} catch (e) {
reject(e);
}
});
}
/**
* Scraped By AETHER
* Protected By MIT LICENSE
* Whoever caught removing wm will be sued
* @param {String} prompt
* @param { String} system
* @description Any Request? Contact me : aetherscode@gmail.com
* @author AETHER 2024
* @copyright https://aetherz.xyz
*/
async function omniplexAi(
prompt,
system = "You are an Ai Asistant that is destinated to help user with their problems"
) {
return new Promise(async (resolve, reject) => {
try {
const BASE_URL = "https://omniplex.ai/api";
const headers = {
origin: BASE_URL.replace("/api", ""),
"user-agent":
"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/126.0.0.0 Safari/537.36",
"Content-Type": "application/json",
};
const chatJSON = {
frequency_penalty: 0,
max_tokens: 512,
messages: [
{
role: "system",
content: system,
},
{
role: "user",
content: prompt,
},
],
model: "gpt-3.5-turbo",
presence_penalty: 0,
temperature: 1,
top_p: 1,
};
// ? Determine which mode
const { mode, arg } = await fetch(BASE_URL + "/tools", {
method: "POST",
headers,
body: JSON.stringify(chatJSON.messages),
}).then((v) => v.json());
// ? Run by mode type
switch (mode) {
case "search": {
const a = await searchMode();
if (!a[0]) reject("Search mode failed with error : \n" + a[1] || a);
return resolve({
mode,
data: a[0],
search: a[1],
});
break;
}
case "chat": {
const b = await chat();
if (!b[0]) reject("Chat mode failed with error : \n" + b[1] || b);
return resolve({
mode,
data: b,
});
break;
}
}
// ? Handler
async function chat() {
return new Promise(async (s, r) => {
try {
const a = await fetch(BASE_URL + "/chat", {
method: "POST",
headers,
body: JSON.stringify(chatJSON),
}).then((v) => v.text());
if (!a) return r([false, "Failed to get result"]);
s(a);
} catch (e) {
r(e);
}
});
}
async function searchMode() {
return new Promise(async (s, r) => {
try {
const a = await fetch(
BASE_URL +
"/search?" +
new URLSearchParams({
q: "search" + prompt,
limit: 5,
})
).then((v) => v.json());
if (a.message !== "Success") return r([false, "Failed to search"]);
const b = a.data.webPages.value.map((v) => v.url);
const c = await fetch(
BASE_URL +
"/scrape?" +
new URLSearchParams({
urls: b.join(","),
}),
{
method: "POST",
headers,
}
).then((v) => v.text());
chatJSON.messages[1].content = c + "\n\nQuestion : " + prompt;
chatJSON.messages[0].content = `Generate a comprehensive and informative answer (but no more than 256 words in 2 paragraphs) for a given question solely based on the provided web Search Results (URL and Summary).You must only use information from the provided search results.Use an unbiased and journalistic tone.Use this current date and time: ${new Date().toUTCString()}.Combine search results together into a coherent answer.Do not repeat text.Only cite the most relevant results that answer the question accurately.If different results refer to different entities with the same name, write separate answers for each entity.You have the ability to search and will be given websites and the scarped data from them and you will have to make up an answer with that only. ${system}`;
const d = await fetch(BASE_URL + "/chat", {
method: "POST",
headers,
body: JSON.stringify(chatJSON),
}).then((v) => v.text());
s([d, a.data]);
} catch (e) {
// r(e);
}
});
}
} catch (e) {
reject([false, e]);
}
});
}
module.exports = { Ai, stableDiff, animagine, omniplexAi };