endolith

from __future__ import division
from numpy.fft import rfft
from numpy import argmax, mean, diff, log, nonzero
from scipy.signal import blackmanharris, correlate
from time import time
import sys
try:
    import soundfile as sf
except ImportError:
    from scikits.audiolab import flacread

brianjp93

bonzanini

# This code uses Biopython to retrieve lists of articles from pubmed
# you need to install Biopython first.

# If you use Anaconda:
# conda install biopython

# If you use pip/venv:
# pip install biopython

# Full discussion:

rbnpi

#Program to drive Sonic Pi 3 visualiser written in "processing"
#by Robin Newman, September 2017
#see article at https://rbnrpi.wordpress.com
#set up OSC address of processing sketch
use_osc '127.0.0.1',5000
#select shapes to show
osc "/viz/shapes","e"  #"s" "e" "r" Star,Ellipse, Rectangle or combination
sleep 0.1

live_loop :c do

Piasy

brew options ffmpeg

brew install ffmpeg \
--with-chromaprint \
--with-fdk-aac \
--with-fontconfig \
--with-freetype \
--with-frei0r \
--with-game-music-emu \
--with-libass \

IanColdwater

Mute these words in your settings here: https://twitter.com/settings/muted_keywords

ActivityTweet
generic_activity_highlights
generic_activity_momentsbreaking
RankedOrganicTweet
suggest_activity
suggest_activity_feed
suggest_activity_highlights
suggest_activity_tweet

ninehills

ninehills

goldengrape

from langchain.callbacks.base import BaseCallbackHandler
import azure.cognitiveservices.speech as speechsdk
import os
import base64
import time
class StreamDisplayHandler(BaseCallbackHandler):
    def __init__(self, container, initial_text="", display_method='markdown'):
        self.container = container
        self.text = initial_text
        self.display_method = display_method

JimLiu

// WARNING：此脚本仅做学习和演示用途，在不了解其用途前不建议使用
// 本脚本的用途是将输入内容分页，每次提取一页内容，编辑第二条消息，发送，然后收集结果
// 使用前，需要有两条消息，参考模板 https://chat.openai.com/share/17195108-30c2-4c62-8d59-980ca645f111
// 演示视频： https://www.bilibili.com/video/BV1tp4y1c7ME/?vd_source=e71f65cbc40a72fce570b20ffcb28b22
// 
(function (fullText) {
  const wait = (ms) => new Promise((resolve) => setTimeout(resolve, ms));

  const groupSentences = (fullText, maxCharecters = 2800) => {
    const sentences = fullText.split("\n").filter((line) => line.trim().length > 0);