1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
|
# 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
SPEAKPATH = '/home/olpc/Activities/Speak.activity'
import os
from gettext import gettext as _
if not os.path.exists(SPEAKPATH):
tw.lc.heap.append(_('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):
print 'brain_respond', kernel
if kernel is not None:
text = kernel.respond(text)
print text
if kernel is None or not text:
text = _("Sorry, I can't understand what you are asking about.")
return text
def brain_load(kernel, voice, sorry=None):
brain = BOTS[voice.friendlyname]
kernel = aiml.Kernel()
if brain['brain'] is None:
warning = _("Sorry, there is no free memory to load my brain. \
Close other activities and try once more.")
print warning
return kernel, None
kernel.loadBrain(brain['brain'])
for name, value in brain['predicates'].items():
kernel.setBotPredicate(name, value)
return kernel, 'load complete'
kernel = None
voice = get_default_voice()
kernel, load_text = brain_load(kernel, voice, None)
response_text = brain_respond(kernel, text)
tw.lc.heap.append(response_text)
return
|