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# A Turtle Block based on the Speak Activity interface to AIML
# Copyright 2012 Walter Bender, Sugar Labs
#
# Copyright (C) 2008 Sebastian Silva Fundacion FuenteLibre
# sebastian@fuentelibre.org
#
# Style and structure taken from Speak.activity Copyright (C) Joshua Minor
#
# HablarConSara.activity is free software: you can redistribute it
# and/or modify it under the terms of the GNU General Public
# License as published by the Free Software Foundation, either
# version 3 of the License, or (at your option) any later version.
#
# HablarConSara.activity is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public
# License along with HablarConSara.activity. If not, see
# <http://www.gnu.org/licenses/>.
def myblock(tw, text):
''' Dialog with AIML library: Usage: Load this code into a Python
Block. Pass text as an argument and the robot's response will
be pushed to the stack. Use a Pop Block to pop the response
off the the stack.'''
# The AIML library is bundled with the Speak activity
SPEAKPATHS = ['/home/olpc/Activities/Speak.activity',
'/home/liveuser/Activities/Speak.activity',
'/usr/share/sugar/activities/Speak.activity']
import os
from gettext import gettext as _
speakpath = None
for sp in SPEAKPATHS:
if os.path.exists(sp):
speakpath = sp
break
if speakpath is None:
tw.showlabel(
'status', _('Please install the Speak Activity and try again.'))
return
import sys
sys.path.append(speakpath)
import gobject
import aiml
import voice
BOTS = {
_('Spanish'): { 'name': 'Sara',
'brain': os.path.join(speakpath, 'bot', 'sara.brn'),
'predicates': { 'nombre_bot': 'Sara',
'botmaster': 'La comunidad Azucar' } },
_('English'): { 'name': 'Alice',
'brain': os.path.join(speakpath, 'bot', 'alice.brn'),
'predicates': { 'name': 'Alice',
'master': 'The Sugar Community' } } }
def get_mem_info(tag):
meminfo = file('/proc/meminfo').readlines()
return int([i for i in meminfo if i.startswith(tag)][0].split()[1])
# load Standard AIML set for restricted systems
if get_mem_info('MemTotal:') < 524288:
mem_free = get_mem_info('MemFree:') + get_mem_info('Cached:')
if mem_free < 102400:
BOTS[_('English')]['brain'] = None
else:
BOTS[_('English')]['brain'] = os.path.join(speakpath, 'bot',
'alisochka.brn')
def get_default_voice():
default_voice = voice.defaultVoice()
if default_voice.friendlyname not in BOTS:
return voice.allVoices()[_('English')]
else:
return default_voice
def brain_respond(kernel, text):
if kernel is not None:
text = kernel.respond(text)
if kernel is None or not text:
text = ''
tw.showlabel(
'status',
_("Sorry, I can't understand what you are asking about."))
return text
def brain_load(kernel, voice):
brain = BOTS[voice.friendlyname]
kernel = aiml.Kernel()
if brain['brain'] is None:
tw.showlabel(
'status', _('Sorry, there is no free memory to load my brain. \
Close other activities and try once more.'))
return kernel
kernel.loadBrain(brain['brain'])
for name, value in brain['predicates'].items():
kernel.setBotPredicate(name, value)
return kernel
kernel = None
if not hasattr(tw, 'aiml_kernel'):
tw.aiml_kernel = brain_load(tw, get_default_voice())
response_text = brain_respond(tw.aiml_kernel, text)
tw.lc.heap.append(response_text)
return
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