Source code for chatterbot.storage.mongodb
import re
from random import randint
from chatterbot.storage import StorageAdapter
[docs]
class MongoDatabaseAdapter(StorageAdapter):
"""
The MongoDatabaseAdapter is an interface that allows
ChatterBot to store statements in a MongoDB database.
:keyword database_uri: The URI of a remote instance of MongoDB.
This can be any valid
`MongoDB connection string <https://docs.mongodb.com/manual/reference/connection-string/>`_
:type database_uri: str
.. code-block:: python
database_uri='mongodb://example.com:8100/'
"""
def __init__(self, **kwargs):
super().__init__(**kwargs)
from pymongo import MongoClient
from pymongo.errors import OperationFailure
self.database_uri = kwargs.get(
'database_uri', 'mongodb://localhost:27017/chatterbot-database'
)
# Use the default host and port
self.client = MongoClient(self.database_uri)
# Increase the sort buffer to 42M if possible
try:
self.client.admin.command({'setParameter': 1, 'internalQueryExecMaxBlockingSortBytes': 44040192})
except OperationFailure:
pass
# Specify the name of the database
self.database = self.client.get_database()
# The mongo collection of statement documents
self.statements = self.database['statements']
[docs]
def get_statement_model(self):
"""
Return the class for the statement model.
"""
from chatterbot.conversation import Statement
# Create a storage-aware statement
statement = Statement
statement.storage = self
return statement
[docs]
def count(self):
return self.statements.count_documents({})
[docs]
def mongo_to_object(self, statement_data):
"""
Return Statement object when given data
returned from Mongo DB.
"""
Statement = self.get_model('statement')
statement_data['id'] = statement_data['_id']
return Statement(**statement_data)
[docs]
def filter(self, **kwargs):
"""
Returns a list of statements in the database
that match the parameters specified.
"""
import pymongo
page_size = kwargs.pop('page_size', 1000)
order_by = kwargs.pop('order_by', None)
tags = kwargs.pop('tags', [])
exclude_text = kwargs.pop('exclude_text', None)
exclude_text_words = kwargs.pop('exclude_text_words', [])
persona_not_startswith = kwargs.pop('persona_not_startswith', None)
search_text_contains = kwargs.pop('search_text_contains', None)
if tags:
kwargs['tags'] = {
'$in': tags
}
if exclude_text:
if 'text' not in kwargs:
kwargs['text'] = {}
elif 'text' in kwargs and isinstance(kwargs['text'], str):
text = kwargs.pop('text')
kwargs['text'] = {
'$eq': text
}
kwargs['text']['$nin'] = exclude_text
if exclude_text_words:
if 'text' not in kwargs:
kwargs['text'] = {}
elif 'text' in kwargs and isinstance(kwargs['text'], str):
text = kwargs.pop('text')
kwargs['text'] = {
'$eq': text
}
exclude_word_regex = '|'.join([
'.*{}.*'.format(word) for word in exclude_text_words
])
kwargs['text']['$not'] = re.compile(exclude_word_regex)
if persona_not_startswith:
if 'persona' not in kwargs:
kwargs['persona'] = {}
elif 'persona' in kwargs and isinstance(kwargs['persona'], str):
persona = kwargs.pop('persona')
kwargs['persona'] = {
'$eq': persona
}
kwargs['persona']['$not'] = re.compile('^bot:*')
if search_text_contains:
or_regex = '|'.join([
'{}'.format(re.escape(word)) for word in search_text_contains.split(' ')
])
kwargs['search_text'] = re.compile(or_regex)
mongo_ordering = []
if order_by:
# Sort so that newer datetimes appear first
if 'created_at' in order_by:
order_by.remove('created_at')
mongo_ordering.append(('created_at', pymongo.DESCENDING, ))
for order in order_by:
mongo_ordering.append((order, pymongo.ASCENDING))
total_statements = self.statements.count_documents(kwargs)
for start_index in range(0, total_statements, page_size):
if mongo_ordering:
for match in self.statements.find(kwargs).sort(mongo_ordering).skip(start_index).limit(page_size):
yield self.mongo_to_object(match)
else:
for match in self.statements.find(kwargs).skip(start_index).limit(page_size):
yield self.mongo_to_object(match)
[docs]
def create(self, **kwargs):
"""
Creates a new statement matching the keyword arguments specified.
Returns the created statement.
"""
Statement = self.get_model('statement')
if 'tags' in kwargs:
kwargs['tags'] = list(set(kwargs['tags']))
if 'search_text' not in kwargs:
kwargs['search_text'] = self.tagger.get_text_index_string(kwargs['text'])
if 'search_in_response_to' not in kwargs:
if kwargs.get('in_response_to'):
kwargs['search_in_response_to'] = self.tagger.get_text_index_string(kwargs['in_response_to'])
inserted = self.statements.insert_one(kwargs)
kwargs['id'] = inserted.inserted_id
return Statement(**kwargs)
[docs]
def create_many(self, statements):
"""
Creates multiple statement entries.
"""
create_statements = []
# Check if any statements already have a search text
have_search_text = any(statement.search_text for statement in statements)
# Generate search text values in bulk
if not have_search_text:
search_text_documents = self.tagger.as_nlp_pipeline([statement.text for statement in statements])
response_search_text_documents = self.tagger.as_nlp_pipeline([statement.in_response_to or '' for statement in statements])
for statement, search_text_document, response_search_text_document in zip(
statements, search_text_documents, response_search_text_documents
):
statement.search_text = search_text_document._.search_index
statement.search_in_response_to = response_search_text_document._.search_index
for statement in statements:
statement_data = statement.serialize()
tag_data = list(set(statement_data.pop('tags', [])))
statement_data['tags'] = tag_data
create_statements.append(statement_data)
self.statements.insert_many(create_statements)
[docs]
def update(self, statement):
data = statement.serialize()
data.pop('id', None)
data.pop('tags', None)
data['search_text'] = self.tagger.get_text_index_string(data['text'])
if data.get('in_response_to'):
data['search_in_response_to'] = self.tagger.get_text_index_string(data['in_response_to'])
update_data = {
'$set': data
}
if statement.tags:
update_data['$addToSet'] = {
'tags': {
'$each': statement.tags
}
}
search_parameters = {}
if statement.id is not None:
search_parameters['_id'] = statement.id
else:
search_parameters['text'] = statement.text
search_parameters['conversation'] = statement.conversation
update_operation = self.statements.update_one(
search_parameters,
update_data,
upsert=True
)
if update_operation.acknowledged:
statement.id = update_operation.upserted_id
return statement
[docs]
def get_random(self):
"""
Returns a random statement from the database
"""
count = self.count()
if count < 1:
raise self.EmptyDatabaseException()
random_integer = randint(0, count - 1)
statements = self.statements.find().limit(1).skip(random_integer)
return self.mongo_to_object(list(statements)[0])
[docs]
def remove(self, statement_text):
"""
Removes the statement that matches the input text.
"""
self.statements.delete_one({'text': statement_text})
[docs]
def drop(self):
"""
Remove the database.
"""
self.client.drop_database(self.database.name)
