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import json | |
from threading import Thread | |
from time import sleep | |
import gooey_gui as gui | |
import requests | |
from decouple import config | |
from fastapi import FastAPI | |
from starlette.requests import Request | |
app = FastAPI() |
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""" | |
README: Android UI Automator Script for Hinge App | |
This script automates the process of liking profiles in the Hinge Android app using the uiautomator2 library. It connects to an Android device, scrolls through the app, finds the like button, and presses it, then attempts to send the like. The process repeats in a loop with random delays and scrolls to mimic human behavior. | |
**Requirements:** | |
- Python 3.x | |
- [uiautomator2](https://github.com/openatx/uiautomator2) (`pip install uiautomator2`) | |
- An Android device with USB debugging enabled | |
- Hinge app installed on the device |
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import 'package:http/http.dart' as http; | |
import 'dart:convert'; | |
main() async { | |
var request = http.MultipartRequest( | |
'POST', | |
Uri.parse('https://api.gooey.ai/v3/Lipsync/async/form/'), | |
); | |
request.headers['Authorization'] = 'bearer sk-hhm...POJ'; | |
request.files.add(http.MultipartFile.fromBytes('input_face', [])); |
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from babel.numbers import format_currency | |
# from gooeysite import wsgi | |
# | |
# assert wsgi | |
# import streamlit as gui | |
import plotly.graph_objects as go | |
import pandas as pd |
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FROM python | |
RUN pip install --no-cache-dir furl requests loguru | |
RUN curl -so main.py 'https://gist.githubusercontent.com/devxpy/2abbe49fa2acb6958eb4d828f50c4467/raw/db60e263a7e345bae31869f5e037f1f87bc54b6b/main.py' | |
CMD ["python", "main.py"] |
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let response = await fetch("https://api.gooey.ai/v3/integrations/stream/", { | |
method: "POST", | |
headers: { | |
"Content-Type": "application/json", | |
}, | |
body: JSON.stringify({ | |
// your integration's ID as shown in the Gooey.AI Integrations tab | |
"integration_id": "DEy", | |
// the input text for the bot | |
"input_prompt": "Hello, world!", |
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|MODEL |TEM4A0C37S31SB |TEM4A0C42S41SB |TEM4A0C48S41SB |TEM4A0C60S51SB| | |
|--|--|--|--|--| | |
|RATED VOLTS/PH/HZ |208-230/1/60 | | || | |
|RATINGS(a) |See O.D. Specifications | | || | |
|INDOOR COIL - Type |Plate Fin | | || | |
|Rows - F.P.I. |3 - 14 |3 - 14 |3 - 14 |4 - 14| | |
|Face Area (sq. ft.) |5.50 |5.50 |5.50 |5.91| | |
|Tube Size (in.) |3/8 | | || | |
|Refrigerant Control |TXV | | || | |
|Drain Conn. Size (in. )(b) |3/4 NPT | | || |
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def reposition_object_img_bytes( | |
*, | |
img_bytes: bytes, | |
mask_bytes: bytes, | |
out_size: (int, int) = (512, 512), | |
out_obj_scale: float = 0.2, | |
out_pos_x: float = 4 / 9, | |
out_pos_y: float = 3 / 9, | |
) -> (bytes, bytes): | |
image_cv2 = bytes_to_cv2_img(img_bytes) |
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from llama_index import ( | |
VectorStoreIndex, | |
SimpleWebPageReader, | |
set_global_service_context, | |
ServiceContext, | |
) | |
from llama_index.callbacks import CallbackManager, TokenCountingHandler | |
from llama_index.chat_engine.types import ChatMode | |
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[('https://assets.interplaylearning.com/videos/learning_path/1530282924685_ACDiagnostics3.mp4', | |
3), | |
('https://s3-us-west-1.amazonaws.com/assets.interplay-learning.com/videos/learning_path/1687286505745_0_IntroWhatisHVACRev.mp4', | |
2), | |
('https://s3-us-west-1.amazonaws.com/assets.interplay-learning.com/videos/learning_path/1687286573158_1_HVACoverviewRev.mp4', | |
2), | |
('https://s3-us-west-1.amazonaws.com/assets.interplay-learning.com/videos/learning_path/1687286713437_2_HVACsystemsRev.mp4', | |
2), | |
('https://s3-us-west-1.amazonaws.com/assets.interplay-learning.com/videos/learning_path/1687293233864_3_SystemComponentsRev.mp4', | |
2), |
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