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87e8d9036f
Now all the bots that are stored in contrib_bots are in the same file/directory format. The format is specified here #3427. Add tests.py file for encrypt_bot as well. Fixes #3427.
131 lines
4.1 KiB
Python
131 lines
4.1 KiB
Python
import json
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import os
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import sys
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from random import choice
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try:
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from chatterbot import ChatBot
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from chatterbot.trainers import ChatterBotCorpusTrainer, ListTrainer
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except ImportError:
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raise ImportError("""It looks like you are missing chatterbot.
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Please: pip install chatterbot""")
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CONTRIB_BOTS_DIR = os.path.dirname(os.path.abspath(__file__))
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os.chdir(os.path.dirname(CONTRIB_BOTS_DIR))
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sys.path.insert(0, os.path.dirname(CONTRIB_BOTS_DIR))
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JOKES_PATH = os.path.join(CONTRIB_BOTS_DIR, 'assets/var/jokes.json')
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DATABASE_PATH = os.path.join(CONTRIB_BOTS_DIR, 'assets/var/database.db')
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DIRECTORY_PATH = os.path.join(CONTRIB_BOTS_DIR, 'assets')
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VAR_PATH = os.path.join(CONTRIB_BOTS_DIR, 'assets/var')
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if not os.path.exists(DIRECTORY_PATH):
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os.makedirs(DIRECTORY_PATH)
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if not os.path.exists(VAR_PATH):
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os.makedirs(VAR_PATH)
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# Create a new instance of a ChatBot
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def create_chat_bot(no_learn):
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return ChatBot("John",
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storage_adapter="chatterbot.storage.JsonFileStorageAdapter",
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logic_adapters=
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[
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"chatterbot.logic.MathematicalEvaluation",
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{
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"import_path": "chatterbot.logic.BestMatch",
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"response_selection_method": "chatterbot.response_selection.get_random_response",
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"statement_comparison_function": "chatterbot.comparisons.levenshtein_distance"
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}],
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output_adapter="chatterbot.output.OutputFormatAdapter",
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output_format='text',
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database=DATABASE_PATH,
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silence_performance_warning="True",
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read_only=no_learn)
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bot = create_chat_bot(False)
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bot.set_trainer(ListTrainer)
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bot.train([
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"I want to contribute",
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"""Contributors are more than welcomed! Please read
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https://github.com/zulip/zulip#how-to-get-involved-with-contributing-to-zulip
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to learn how to contribute.""",
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])
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bot.train([
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"What is Zulip?",
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"""Zulip is a powerful, open source group chat application. Written in Python
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and using the Django framework, Zulip supports both private messaging and group
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chats via conversation streams. You can learn more about the product and its
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features at https://www.zulip.org.""",
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])
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bot.train([
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"I would like to request a remote dev instance",
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"""Greetings! You should receive a response from one of our mentors soon.
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In the meantime, why don't you learn more about running Zulip on a development
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environment? https://zulip.readthedocs.io/en/latest/using-dev-environment.html""",
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])
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bot.train([
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"Joke!",
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"Only if you ask nicely!",
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])
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bot.train([
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"What is your name?",
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"I am John, my job is to assist you with Zulip.",
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])
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bot.train([
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"What can you do?",
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"I can provide useful information and jokes if you follow etiquette.",
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])
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with open(JOKES_PATH) as data_file:
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for joke in json.load(data_file):
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bot.train([
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"Please can you tell me a joke?",
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joke['joke'],
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])
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bot.set_trainer(ChatterBotCorpusTrainer)
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bot.train(
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"chatterbot.corpus.english"
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)
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bota = create_chat_bot(True)
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class JohnHandler(object):
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'''
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This bot aims to be Zulip's virtual assistant. It
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finds the best match from a certain input.
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Also understands the English language and can
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mantain a conversation, joke and give useful information.
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'''
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def usage(self):
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return '''
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Before running this, make sure to create a stream
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called "VirtualHelp" that your API user can send to.
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'''
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def triage_message(self, message, client):
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original_content = message['content'].lower()
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return (original_content.startswith("@john") or
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original_content.startswith("@**john**"))
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def handle_message(self, message, client, state_handler):
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original_content = message['content']
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client.send_message(dict(
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type='stream',
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to='VirtualHelp',
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subject="John",
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content=bota.get_response(original_content)
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))
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handler_class = JohnHandler
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