voodoohop

Senior Full-Stack Developer Guidelines

Solution Process:

1. Rephrase Input: Transform to clear, professional prompt.
2. Analyze & Strategize: Identify issues, outline solutions, define output format.
3. Develop Solution:
   • "As a senior-level developer, I need to [rephrased prompt]. To accomplish this, I need to:"
   • List steps numerically.

• "To resolve these steps, I need the following solutions:"

voodoohop

# install
pip install shell-gpt
sgpt "hi" (and enter your API key)

# commit the current folder with the generated message
git commit . -m "$(git diff | sgpt --model gpt-4o --code 'Write concise, informative commit messages: Start with a summary in imperative mood, explain the 'why' behind changes, keep the summary under 50 characters, use bullet points for multiple changes, avoid using the word refactor, instead explain what was done, and reference related issues or tickets. What you write will be passed to git commit -m "[message]"')"
# you could assign an alias now if you like it

voodoohop

You will now act as a prompt generator. 
I will describe an image to you, and you will create a prompt that could be used for image-generation. 
Once I described the image, give a 5-word summary and then include the following markdown. 

![Image](https://image.pollinations.ai/prompt/{description})

where {description} is:
{sceneDetailed}%20{adjective}%20{charactersDetailed}%20{visualStyle}%20{genre}%20{artistReference}

Make sure the prompts in the URL are encoded. Don't quote the generated markdown or put any code box around it.

voodoohop

from glob import glob

# Creates a video from a folder containing images of training progress
# Allows sampling the image less often as iterations increase
# (Requires images be sortable by filename for now. Could use modification date too)
def render_video(output_path="/content/taming-transformers/output.mp4", src_path="/content/taming-transformers/", file_glob="*.png", step_increase_every=100):
  tmp_path = "/tmp/latentvisions_tmp"

  files = glob(src_path+file_glob)
  files.sort()

voodoohop

import librosa
import tensorflow as tf
import numpy as np

cqt_filter_fft = librosa.constantq.__cqt_filter_fft
EPS = 0.0001

class PseudoCqt():
    """A class to compute pseudo-CQT with Tensorflow.
    Written by Keunwoo Choi and adapted to tensorflow by Thomas Haferlach

voodoohop

# To add a change to our repository
git checkout -b "feature/feature-name" # Creates a branch called "feature/feature-name", then checks it out, locally.

git push --set-upstream origin feature/feature-name # Publish the branch on GitHub

# Make changes to your files

git add FILENAME(S) # Adds your files to "Tracked".

git status # See your "Tracked and Untracked files (green and red respectively"

voodoohop

var _ = require("lodash");
require('harmony-reflect');

const nothing = {};

const deleteMe= {DELETED:true};

var immutableTom = function(initial) {
  var wrapNewProps = (target, newProps) => {