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model = load_model("/random_forest_model.pkl")

try:
    sepal_length, sepal_width, petal_length, petal_width = parse_comment_input(args.issue_comment_body)
    predicted_class_id = make_prediction(model, sepal_length, sepal_width, petal_length, petal_width)
    predicted_class_name = map_class_id_to_name(predicted_class_id)
    reply_message = f"Hey @{args.issue_user}!<br>This was your input: {args.issue_comment_body}.<br>The prediction: **{predicted_class_name}**"
except Exception as e:
    reply_message = f"Hey @{args.issue_user}! There was a problem with your input. The error: {e}"

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FROM python:3.6

# Install python requirements
COPY requirements.txt /requirements.txt
RUN pip install -r /requirements.txt

# Setup Docker entrypoint script
COPY entrypoint.sh /entrypoint.sh
RUN chmod +x /entrypoint.sh

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name: Demo
on: [issue_comment]

jobs:
    my_first_job:
        runs-on: ubuntu-latest
        name: Just a simple demo job
        steps:
            - name: Checkout
              uses: actions/checkout@master

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name: 'Prediction GitHub Action Test'
description: 'This is a sample with which you can run inference on a ML model with a toy dataset'
inputs:
  issue_comment_body:
    required: true
    description: 'This is the Github issue comment message'
  issue_number:
     required: true
     description: 'Number of the Github issue'
  issue_user:

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mkdir opencv
cd opencv

sudo apt-get update -y && sudo apt-get upgrade -y
sudo apt-get install build-essential cmake pkg-config -y
sudo apt-get install libjpeg-dev libtiff5-dev libjasper-dev libpng12-dev -y
sudo apt-get install libavcodec-dev libavformat-dev libswscale-dev libv4l-dev -y
sudo apt-get install libxvidcore-dev libx264-dev -y
sudo apt-get install libgtk2.0-dev libgtk-3-dev -y
sudo apt-get install libatlas-base-dev gfortran -y

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RebotKit basic Info

• Name/Név: RebotKit
• Hashtag: #Rebot #RebotKit
• Webpage/Honlap: rebotkit.net
• LinkedIn: linkedin.com/company/rebotkit
• Facebook: https://www.facebook.com/rebotkit
• Slogan: Don't throw it out, create a Rebot!
• Promotional Images/Promóciók képek: Contact us via the contact info at our webpage

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import threading

import cv2


class Camera(object):
    """
    Base Camera object
    """

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import re

import nltk
import pandas as pd
from nltk.stem.snowball import SnowballStemmer
from sklearn.cluster import DBSCAN
from sklearn.feature_extraction.text import TfidfVectorizer

df = pd.read_csv("data/movie_metadata.csv", header=0)