NeuroGPT / g4f /Provider /DeepAi.py
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from __future__ import annotations
import json
import js2py
from aiohttp import ClientSession
from ..typing import AsyncGenerator
from .base_provider import AsyncGeneratorProvider
class DeepAi(AsyncGeneratorProvider):
url: str = "https://deepai.org"
working = True
supports_gpt_35_turbo = True
@staticmethod
async def create_async_generator(
model: str,
messages: list[dict[str, str]],
proxy: str = None,
**kwargs
) -> AsyncGenerator:
token_js = """
var agent = 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/115.0.0.0 Safari/537.36'
var a, b, c, d, e, h, f, l, g, k, m, n, r, x, C, E, N, F, T, O, P, w, D, G, Q, R, W, I, aa, fa, na, oa, ha, ba, X, ia, ja, ka, J, la, K, L, ca, S, U, M, ma, B, da, V, Y;
h = Math.round(1E11 * Math.random()) + "";
f = function () {
for (var p = [], q = 0; 64 > q;) p[q] = 0 | 4294967296 * Math.sin(++q % Math.PI);
return function (t) {
var v, y, H, ea = [v = 1732584193, y = 4023233417, ~v, ~y],
Z = [],
A = unescape(encodeURI(t)) + "\u0080",
z = A.length;
t = --z / 4 + 2 | 15;
for (Z[--t] = 8 * z; ~z;) Z[z >> 2] |= A.charCodeAt(z) << 8 * z--;
for (q = A = 0; q < t; q += 16) {
for (z = ea; 64 > A; z = [H = z[3], v + ((H = z[0] + [v & y | ~v & H, H & v | ~H & y, v ^ y ^ H, y ^ (v | ~H)][z = A >> 4] + p[A] + ~~Z[q | [A, 5 * A + 1, 3 * A + 5, 7 * A][z] & 15]) << (z = [7, 12, 17, 22, 5, 9, 14, 20, 4, 11, 16, 23, 6, 10, 15, 21][4 * z + A++ % 4]) | H >>> -z), v, y]) v = z[1] | 0, y = z[2];
for (A = 4; A;) ea[--A] += z[A]
}
for (t = ""; 32 > A;) t += (ea[A >> 3] >> 4 * (1 ^ A++) & 15).toString(16);
return t.split("").reverse().join("")
}
}();
"tryit-" + h + "-" + f(agent + f(agent + f(agent + h + "x")));
"""
payload = {"chas_style": "chat", "chatHistory": json.dumps(messages)}
api_key = js2py.eval_js(token_js)
headers = {
"api-key": api_key,
"User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/115.0.0.0 Safari/537.36",
}
async with ClientSession(
headers=headers
) as session:
async with session.post("https://api.deepai.org/make_me_a_pizza", proxy=proxy, data=payload) as response:
response.raise_for_status()
async for stream in response.content.iter_any():
if stream:
yield stream.decode()