ymoslem

# pip3 install openai

import openai
import time


OPENAI_API_KEY = "your_api_key_here"
openai.api_key = OPENAI_API_KEY

prompt = """French: La semaine dernière, quelqu’un m’a fait part de sa gratitude envers notre travail.

ktmud

import os

from .app import start_cli_service


env = (os.environ.get("env") or "prod").lower()
is_dev = env == "dev" or env == "local"
port, autoreload_observer = start_cli_service(autoreload=is_dev)
if autoreload_observer:
    # move autoreload observer to the foreground so process won't exit

nielsuit227

import React, {useEffect, useRef, useState} from 'react';
import { Switch, Flex, Text } from '@chakra-ui/react';
import UplotReact from 'uplot-react';
import { toast } from 'react-toastify';
import 'uplot/dist/uPlot.min.css';


const colors = [
    '#007BFF',
    '#FFA62B', 

okld

import streamlit as st
from persist import persist, load_widget_state


def main():
    if "page" not in st.session_state:
        # Initialize session state.
        st.session_state.update({
            # Default page.
            "page": "home",

ines

"""
Example of a Streamlit app for an interactive Prodigy dataset viewer that also lets you
run simple training experiments for NER and text classification.

Requires the Prodigy annotation tool to be installed: https://prodi.gy
See here for details on Streamlit: https://streamlit.io.
"""
import streamlit as st
from prodigy.components.db import connect
from prodigy.models.ner import EntityRecognizer, merge_spans, guess_batch_size

sloanlance

jq: JSONL ↔︎ JSON conversion

Prerequisites

• jq — https://jqlang.github.io/jq/ — "like sed for JSON data"

  There are several options available for installing jq. I prefer to use Homebrew: brew install jq

1. JSONL → JSON

ilblackdragon

import logging

import numpy as np
import tensorflow as tf
from tensorflow.contrib import layers


GO_TOKEN = 0
END_TOKEN = 1
UNK_TOKEN = 2

adamfeuer

d3js Tree Visualizer

This example pulls together various examples of work with trees in D3.js. See the d3js Tree Visualizer live here.

The panning functionality can certainly be improved in my opinion and I would be thrilled to see better solutions contributed.

One can do all manner of housekeeping or server related calls on the drop event to manage a remote tree dataset for example.

Panning can either be done by dragging an empty part of the SVG around or dragging a node towards an edge.

oakes

Contents

• Why care about Rust?
• The Toolchain
• Creating a New Project
• Modules
• Crates
• Types
• References
• Mutability

Nazgolze

#!/usr/bin/python2

import logging
import sys
import couchdb
import json
from libgreader import GoogleReader, ClientAuthMethod, Feed

"""
Original can be obtained here: https://gist.github.com/Nazgolze/5479539