Alan Nichol amn41

Comment on a GitHub PR with Rasa NLU cross-validation results

Save the yaml file at .github/workflows/comment_crossval_results.yml

Add the format_results.py script at the root of your repo.

	function gpt() {
	local url="https://api.openai.com/v1/chat/completions"
	local model="gpt-3.5-turbo"
	local body="{\"model\":\"$model\", \"messages\":[{\"role\": \"user\", \"content\": \"$1\"}]}"
	local headers="Content-Type: application/json"
	local auth="Authorization: Bearer ${OPENAI_API_KEY}"

	curl -s -H "$headers" -H "$auth" -d "$body" "$url" \
	\| jq -r '.choices[0].message.content'
	}

	import streamlit as st
	import numpy as np
	import pandas as pd
	import json
	import requests

	@st.cache
	def get_auth_token(host, user, pw):
	st.write("cache miss token!")
	url = f"{host}/api/auth"

	import json
	import requests

	def get_auth_token(host, user, pw):
	url = f"{host}/api/auth"
	payload = {"username": user, "password": pw}
	response = requests.post(url, json=payload)
	try:
	token = response.json()["access_token"]
	return token

	from __future__ import absolute_import
	from __future__ import division
	from __future__ import print_function
	from __future__ import unicode_literals

	import logging

	from flask import Blueprint, request, jsonify
	import requests
	from rasa_dm.channels.channel import UserMessage, OutputChannel

	from rasa_dm.actions import Action
	import requests

	class ActionHTTPRequest(Action):
	def name(self):
	return "make_request"

	def run(self, dispatcher, tracker, domain):
	url = 'https://query.yahooapis.com/v1/public/yql?q=select%20*%20from%20weather.forecast%20where%20woeid%20in%20(select%20woeid%20from%20geo.places(1)%20where%20text%3D%22nome%2C%20ak%22)&format=json'
	result = requests.get(url).json()

	"""Implements the long-short term memory character model.
	This version vectorizes over multiple examples, but each string
	has a fixed length."""

	from __future__ import absolute_import
	from __future__ import print_function
	from builtins import range
	from os.path import dirname, join
	import numpy as np
	import numpy.random as npr

	import rinocloud as rino
	import shutil, os
	import subprocess
	import hashlib

	"""
	persist = Persistor(config.rino_token,config.rino_dir)

	def save_model_new(persist,model_file,score):
	temp_file="tmp_{0:06d}.txt".format(random.choice(range(10000)))