Comment on a GitHub PR with Rasa NLU cross-validation results
Instructions
Save the yaml
file at .github/workflows/comment_crossval_results.yml
Add the format_results.py
script at the root of your repo.
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() |
from __future__ import unicode_literals | |
from __future__ import print_function | |
from __future__ import division | |
from __future__ import absolute_import | |
from builtins import str as text | |
import argparse | |
import io | |
import 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))) |
import numpy as np | |
def sum_vecs(embed,text): | |
tokens = text.split(' ') | |
vec = np.zeros(embed.W.shape[1]) | |
for idx, term in enumerate(tokens): | |
if term in embed.vocab: | |
vec = vec + embed.W[embed.vocab[term], :] |