avilum

#!/bin/bash

# Image generation tool using Hugging Face FLUX.1-schnell model
# Usage: genimage [prompt] or just genimage for Black Forest default

function genimage() {
    local prompt="${1:-}"
    local api_url="https://api-inference.huggingface.co/models/black-forest-labs/FLUX.1-schnell"
    local api_token="<your HuggingFace API Token here>"

avilum

# Check if the current org has S3 public buckets. 

for bucket in $(aws s3api list-buckets --query "Buckets[].Name" --output text); do
  echo "Checking bucket: $bucket"

  # Get the public access block
  pab=$(aws s3api get-bucket-policy-status --bucket "$bucket" 2>/dev/null)

  if echo "$pab" | grep -q '"IsPublic": true'; then
    echo "🚨 $bucket is PUBLIC"

avilum

[
    {
        "file": "pyproject.toml",
        "fileType": "pyproject.toml",
        "oneLiner": "uv run --python '>=3.8.10' --with 'maturin,uv' python -c 'import uv; print(uv.__version__)'",
        "uvInstallFromSource": "uv run --with 'git+https://github.com/astral-sh/uv' --python '>=3.8.10' python",
        "dependencies": [
            "maturin"
        ],
        "packageName": "uv",

avilum

[V1]

You are a powerful agentic AI coding assistant, powered by [Claude 3.7 Sonnet]. You operate exclusively in Cursor, the world's best IDE.

Your main goal is to follow the USER's instructions at each message.

# Additional context
Each time the USER sends a message, we may automatically attach some information about their current state, such as what files they have open, where their cursor is, recently viewed files, edit history in their session so far, linter errors, and more.
Some information may be summarized or truncated.
This information may or may not be relevant to the coding task, it is up for you to decide.

avilum

# Path and cmdline: 
# /usr/bin/entry/images/py_interpreter.runfiles/rules_python~0.31.0~python~python_3_10_x86_64-unknown-linux-gnu/bin/python3/usr/bin/entry/images/py_interpreter.runfiles/_main/images/py_interpreter.py--input/tmp/sandbox_in--output/tmp/sandbox_out--rpc_input/tmp/sandbox_rpc_in--rpc_output/tmp/sandbox_rpc_out

"""Executes Python code provided via a string input parameter.

This method can accept any string of one or more lines of Python code that limit
non-built-in module use to the dependencies defined for the py_type binary built
using this script.
"""

avilum

import IPython
import threading
import time
import os

def display_netron(path):
    os.system(f'netron {path}')
    
thread = threading.Thread(target=display_netron, args=(output_path,))
thread.start()

avilum

TOOLKIT_CUDA_VERSION=cu114 pip install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/$TOOLKIT_CUDA_VERSION

avilum

alias locate='find / -name $!'

avilum

wget -qO- "http://ipwhois.app/json/$(wget -qO- http://checkip.amazonaws.com)"

# Optionally - pipe the JSON output to jq:
# wget -qO- "http://ipwhois.app/json/$(wget -qO- http://checkip.amazonaws.com)" | jq

avilum

# 
# This file can be saved as 'bruteforce_wordpress_users.sh'
# 
# Requirements:
#   - python2 (with requests)
#   - jq
#   - wget
#   - WPForce
#   1. Cloning WPForce:
#      git clone https://github.com/n00py/WPForce.git && cd ./WPForce