Contrôlé par mes jambes en bas noirs
3,003 94%
,jpeg/024/665/174/1280x720.17160293.jpg)
Hello, I can see you being so small, but that's OK as long as a part of you is to My liking. I want to let you know that this clip is going to condition you to become My most devoted hosiery slave, it's going to turn your fetish into something more intense. Are you ready to discover what it's like to be completely devoted to Me? To let Me blow your mind? So you're here voluntarily because you can't take your eyes off My sultry legs. I'm going to put you into a mild trance, which will allow you to develop new thoughts, that make you even weaker for Me and more desperate to worship My stocking legs. Before, you were just a wanker online. I'm going to turn you into My most addicted wanker by using My gorgeous body, My beautiful legs and My exquisite brain that fascinates you. It's OK to have a few submissive thoughts here and there, however, right now you're going to enter this submissive trance. How you're going to do that? It's extremely easy.
import nltk
from nltk.corpus import wordnet
from googleapiclient.discovery import build
# Ensure you have downloaded the required NLTK data
nltk.download('punkt')
nltk.download('wordnet')
# Set up YouTube API credentials
api_key = 'YOUR_YOUTUBE_API_KEY'
youtube_service = build('youtube', 'v3', developerKey=api_key)
# Define a function to generate videos from a text description
def generate_videos(description):
queries = generate_query_variations(description)
videos = []
for query in queries:
video_results = search_youtube(query)
videos.extend(video_results)
return videos
# Define a function to search for videos using YouTube API
def search_youtube(query):
request = youtube_service.search().list(
q=query,
part='snippet',
maxResults=10 # You can adjust the number of results
)
response = request.execute()
# Extract video details from the response
videos = response.get('items', [])
return videos
# Define a function to generate query variations
def generate_query_variations(description):
variations = []
tokens = nltk.word_tokenize(description)
for token in tokens:
synonyms = wordnet.synsets(token)
for synonym in synonyms:
# Get the synonym name
synonym_name = synonym.lemmas()[0].name()
# Create a query variation by replacing the token with the synonym
variation = description.replace(token, synonym_name)
variations.append(variation)
return variations
# Set up a text input event listener
def on_text_input(event):
description = event.text
videos = generate_videos(description)
update_video_results(videos)
# Integrate with YouTube API search bar (assuming this is part of some UI framework)
# youtube.search_bar.on_text_input = on_text_input
# Define a function to generate videos concurrently
def generate_videos_concurrently(description):
threads = []
queries = generate_query_variations(description)
videos = []
# Function to run in each thread
def search_videos(query):
video_results = search_youtube(query)
videos.extend(video_results)
# Create and start a thread for each query
for query in queries:
thread = threading.Thread(target=search_videos, args=(query,))
threads.append(thread)
thread.start()
# Wait for all threads to finish
for thread in threads:
thread.join()
return videos
# Re