def checkReminders(verbose=False):
from timeParsing import getTimeVec
from determineFunction import updateContext
from emotions import getFace
rotateCircle(index=2, angle=30)
#print "LOADING"
REMINDERS = load(DATA_DIR + "reminders.txt", LPC=1)
REMINDERS = [s[0] for s in REMINDERS]
#print "LOADING... DONE"
#nowTime = getTimeVec("now")
updateReminders = False
NowTime = datetime.datetime.now()
NowTotalSecs = (NowTime - datetime.datetime(1970, 1, 1)).total_seconds()
dueInFuture = 0 # track how many are due in future
textStr = ""
for i in range(len(REMINDERS)):
item = REMINDERS[i]
if item[1] != [] and item[2] != True:
# see if the time has passes:
NoteTime = datetime.datetime(year=item[1][0],
month=item[1][1],
day=item[1][2],
hour=item[1][3],
minute=item[1][4],
second=item[1][5])
NoteTotalSecs = (NoteTime -
datetime.datetime(1970, 1, 1)).total_seconds()
timePassed = (NowTotalSecs >= NoteTotalSecs)
if not timePassed:
dueInFuture += 1
#say("Future: "+item[0], more=True, speak=setting("SPEAK"), moodUpdate=True)
if timePassed:
noteTD = toDict(item[1])
diffStr = timeDiff(noteTD)
rStr = "Reminder: " + item[0] + " (due " + diffStr + ")"
say(rStr,
more=(not setting('SEND_TEXT')),
speak=setting("SPEAK"),
moodUpdate=True)
#say("Reminder: "+item[0], more=True, speak=setting("SPEAK"), moodUpdate=True)
REMINDERS[i] = (item[0], item[1], True)
updateContext(inStr=item[0])
updateReminders = True
textStr = textStr + " <" + item[0] + ">"
if setting('SEND_TEXT') and not textStr == "":
face = getFace(GLOB['MOOD'])
moodStr = ""
if face[0] == "":
moodStr = "(" + getFace(
GLOB['MOOD'])[2] + ")" # use the description
else:
moodStr = getFace(GLOB['MOOD'])[0] # use the emoticon
textStr = setting(
"YOUR_NAME") + " " + moodStr + " REMINDER: " + textStr
say("Sending text...", more=True, speak=False, moodUpdate=True)
sendText(textStr)
if verbose and not updateReminders:
dueStr = "(" + ('%s' % dueInFuture) + " due in future)"
say("No new reminders. " + dueStr,
more=False,
speak=setting("SPEAK"),
moodUpdate=True)
updateContext(inStr="reminders")
return "new prompt"
# want to overwrite ingestions file
if updateReminders:
f = open(DATA_DIR + 'reminders.txt', 'w')
for item in REMINDERS:
userStr = k.cleanWord(item[0], cleanType=1)
f.write("\'%s\', %s, %s\n" % (userStr, item[1], item[2]))
f.close()
return "no prompt"
def checkReminders(verbose=False):
from timeParsing import getTimeVec
from determineFunction import updateContext
from emotions import getFace
rotateCircle(index=2, angle=30)
#print "LOADING"
REMINDERS=load(DATA_DIR+"reminders.txt", LPC=1)
REMINDERS=[s[0] for s in REMINDERS]
#print "LOADING... DONE"
#nowTime = getTimeVec("now")
updateReminders=False
NowTime = datetime.datetime.now()
NowTotalSecs = (NowTime-datetime.datetime(1970,1,1)).total_seconds()
dueInFuture=0 # track how many are due in future
textStr=""
for i in range(len(REMINDERS)):
item = REMINDERS[i]
if item[1] != [] and item[2] != True:
# see if the time has passes:
NoteTime = datetime.datetime(year = item[1][0], month=item[1][1], day=item[1][2], hour=item[1][3], minute=item[1][4], second=item[1][5])
NoteTotalSecs = (NoteTime-datetime.datetime(1970,1,1)).total_seconds()
timePassed = (NowTotalSecs >= NoteTotalSecs)
if not timePassed:
dueInFuture += 1
#say("Future: "+item[0], more=True, speak=setting("SPEAK"), moodUpdate=True)
if timePassed:
noteTD = toDict(item[1])
diffStr = timeDiff(noteTD)
rStr = "Reminder: "+item[0]+" (due "+diffStr+")"
say(rStr, more=(not setting('SEND_TEXT')), speak=setting("SPEAK"), moodUpdate=True)
#say("Reminder: "+item[0], more=True, speak=setting("SPEAK"), moodUpdate=True)
REMINDERS[i] = (item[0], item[1], True)
updateContext(inStr=item[0])
updateReminders=True
textStr=textStr+" <"+item[0]+">"
if setting('SEND_TEXT') and not textStr == "":
face=getFace(GLOB['MOOD'])
moodStr=""
if face[0]=="":
moodStr="("+getFace(GLOB['MOOD'])[2]+")" # use the description
else:
moodStr=getFace(GLOB['MOOD'])[0] # use the emoticon
textStr=setting("YOUR_NAME")+" "+moodStr+" REMINDER: "+textStr
say("Sending text...", more=True, speak=False, moodUpdate=True)
sendText(textStr)
if verbose and not updateReminders:
dueStr = "("+('%s'%dueInFuture)+" due in future)"
say("No new reminders. "+dueStr, more=False, speak=setting("SPEAK"), moodUpdate=True)
updateContext(inStr="reminders")
return "new prompt"
# want to overwrite ingestions file
if updateReminders:
f = open(DATA_DIR+'reminders.txt', 'w')
for item in REMINDERS:
userStr = k.cleanWord(item[0], cleanType=1)
f.write("\'%s\', %s, %s\n" % (userStr, item[1], item[2]))
f.close()
return "no prompt"
def KTInterface(inCmd, inStr, matches=[[], []]):
#print "KTI"
from determineFunction import refineMatches, updateContext
inStr = inStr.replace('\"', '').replace('\'', '')
#matches = refineMatches(inCmd, inStr)
matches = substituteBiographicMemory(matches, queryType='what is')
inStr = inStr.lower()
setFace(face="thinking_animation")
# check if summarizing clipboard
if "clipboard" in inStr and len(matches[0]) == 0:
say("Summarizing data in clipboard.",
more=False,
speak=setting("SPEAK"),
moodUpdate=False,
PAUSE_SEND=True)
CLIPBOARD = k.loadClipboard()
#k.summary(CLIPBOARD, SEN_NUM=3, TYPE="short", CHRON=True)
top5 = k.importantSentences(CLIPBOARD, SEN_NUM=5, CHRON=True)
top5 = [sen[0] for sen in top5]
topTrimmed = []
lenSum = 0
for sen in top5:
if lenSum < 75: # max words
topTrimmed.append(sen)
lenSum += len(sen.split())
else:
break
topStr = ' '.join(topTrimmed)
#print top3Str
tkHistCat(topStr + '\n')
#k.summary(k.loadClipboard())
# now update the context
if len(CLIPBOARD[0]) != 0:
Freqs = k.getWordFreqs(k.filter(CLIPBOARD, lemmatize=True))
if len(Freqs) != 0:
#print "new context: ", Freqs[0][0]
updateContext(inStr=Freqs[0][0])
return True
if len(matches[0]) == 0:
say(getResponse(findCMD("rephrase")),
more=False,
speak=setting("SPEAK"),
moodUpdate=False)
return False
# now figure out query type
if ("in common" in inStr or "similar" in inStr):
if len(matches[0]) != 2:
say("I was expecting two terms to compare.",
more=False,
speak=setting("SPEAK"))
return False
# get the word frequency intersection and return top few words
timedOut = False
try:
A1, A2 = k.learn(matches[0][0]), k.learn(matches[0][1])
except TimedOutExc:
say("Unable to get data from Wikipedia.",
more=False,
speak=setting("SPEAK"))
timedOut = True
return True
pass
if len(A1) <= 2 and not timedOut:
#say("Wikipedia article "+matches[0][0]+" not found.", more=True, speak=setting("SPEAK"))
#sys.stdout.flush()
return False
if len(A2) <= 2 and not timedOut:
#say("Wikipedia article "+matches[0][1]+" not found.", more=True, speak=setting("SPEAK"))
#sys.stdout.flush()
return False
# say something like "let me think about this"
say(getResponse(inCmd),
more=False,
speak=setting("SPEAK"),
PAUSE_SEND=True)
# get the top 3
top3Str = ', '.join([c[0] for c in k.wordIntersection(A1, A2)[0:3]])
strProcessed = processResponse(
"Things #0# and #1# have in common: #2#.",
replacements=[matches[0][0], matches[0][1], top3Str])
say(strProcessed, more=False, speak=setting("SPEAK"))
return True
if ("tell me about" in inStr) or ("know about" in inStr) or (
"teach me" in inStr) or ("learn about" in inStr):
#print "inSTR = ", inStr
retVal = False
for topic in matches[0]: # already checked to be non-zero
timedOut = False
try:
A = k.learn(topic)
#if setting('DEBUG'):
#print A
except: # TimedOutExc:
say("Unable to get data from Wikipedia.",
more=False,
speak=setting("SPEAK"))
timedOut = True
pass
return True
if len(A) <= 2 and not timedOut:
#say("Wikipedia article "+topic+" not found.", more=False, speak=setting("SPEAK"))
retVal = False
else:
say(getResponse(inCmd),
more=False,
speak=setting("SPEAK"),
PAUSE_SEND=True)
# get top 3 sentences on topic
top2 = k.importantSentences(A, SEN_NUM=2, CHRON=True)
topStrs = [sen[0] for sen in top2]
strProcessed = processResponse(
"Let me tell you about \"#0#\": \n\t- #1# #2#",
replacements=[topic, topStrs[0], topStrs[1]])
say(strProcessed, more=False, speak=setting("SPEAK"))
retVal = True
return retVal
if "word web" in inStr:
if len(matches[0]) != 1:
say("I was expecting only one term in \"\"'s.",
more=False,
speak=setting("SPEAK"))
return False
say(getResponse(inCmd),
more=False,
speak=setting("SPEAK"),
PAUSE_SEND=True)
try:
A = k.learn(matches[0][0])
except TimedOutExc:
say("Unable to get data from Wikipedia.",
more=False,
speak=setting("SPEAK"))
pass
return True
except:
pass
return True
if len(A) <= 2:
say("Wikipedia article " + matches[0][0] + " not found.",
more=False,
speak=setting("SPEAK"))
return False
else:
k.wordWeb(A)
return True
if ("draw" in inStr) or ("paint" in inStr) or ("painting" in inStr):
if len(matches[0]) != 1:
say("I was expecting only one term.",
more=False,
speak=setting("SPEAK"))
return False
say(getResponse(inCmd),
more=False,
speak=setting("SPEAK"),
PAUSE_SEND=True)
#print "word:"+qWords[0]
try:
k.paintImage(k.learn(matches[0][0]))
return True
except TimedOutExc:
say("Unable to get data from Wikipedia.",
more=False,
speak=setting("SPEAK"))
pass
return False
return False
def KTInterface(inCmd, inStr, matches=[[],[]]):
#print "KTI"
from determineFunction import refineMatches, updateContext
inStr = inStr.replace('\"', '').replace('\'','')
#matches = refineMatches(inCmd, inStr)
matches = substituteBiographicMemory(matches, queryType='what is')
inStr = inStr.lower()
setFace(face="thinking_animation")
# check if summarizing clipboard
if "clipboard" in inStr and len(matches[0]) == 0:
say("Summarizing data in clipboard.", more=False, speak=setting("SPEAK"), moodUpdate=False, PAUSE_SEND=True)
CLIPBOARD = k.loadClipboard()
#k.summary(CLIPBOARD, SEN_NUM=3, TYPE="short", CHRON=True)
top5=k.importantSentences(CLIPBOARD, SEN_NUM=5, CHRON=True)
top5 = [sen[0] for sen in top5]
topTrimmed = []
lenSum = 0
for sen in top5:
if lenSum < 75: # max words
topTrimmed.append(sen)
lenSum += len(sen.split())
else:
break
topStr = ' '.join(topTrimmed)
#print top3Str
tkHistCat(topStr+'\n')
#k.summary(k.loadClipboard())
# now update the context
if len(CLIPBOARD[0]) != 0:
Freqs = k.getWordFreqs(k.filter(CLIPBOARD, lemmatize=True))
if len(Freqs) != 0:
#print "new context: ", Freqs[0][0]
updateContext(inStr=Freqs[0][0])
return True
if len(matches[0]) == 0:
say(getResponse(findCMD("rephrase")), more=False, speak=setting("SPEAK"), moodUpdate=False)
return False
# now figure out query type
if ("in common" in inStr or "similar" in inStr):
if len(matches[0]) != 2:
say("I was expecting two terms to compare.", more=False, speak=setting("SPEAK"))
return False
# get the word frequency intersection and return top few words
timedOut=False
try:
A1, A2 = k.learn(matches[0][0]), k.learn(matches[0][1])
except TimedOutExc:
say("Unable to get data from Wikipedia.", more=False, speak=setting("SPEAK"))
timedOut = True
return True
pass
if len(A1) <= 2 and not timedOut:
#say("Wikipedia article "+matches[0][0]+" not found.", more=True, speak=setting("SPEAK"))
#sys.stdout.flush()
return False
if len(A2) <= 2 and not timedOut:
#say("Wikipedia article "+matches[0][1]+" not found.", more=True, speak=setting("SPEAK"))
#sys.stdout.flush()
return False
# say something like "let me think about this"
say(getResponse(inCmd), more=False, speak=setting("SPEAK"), PAUSE_SEND=True)
# get the top 3
top3Str=', '.join([c[0] for c in k.wordIntersection(A1, A2)[0:3]])
strProcessed=processResponse("Things #0# and #1# have in common: #2#.", replacements=[matches[0][0], matches[0][1], top3Str])
say(strProcessed, more=False, speak=setting("SPEAK"))
return True
if ("tell me about" in inStr) or ("know about" in inStr) or ("teach me" in inStr) or ("learn about" in inStr):
#print "inSTR = ", inStr
retVal = False
for topic in matches[0]: # already checked to be non-zero
timedOut = False
try:
A = k.learn(topic)
#if setting('DEBUG'):
#print A
except:# TimedOutExc:
say("Unable to get data from Wikipedia.", more=False, speak=setting("SPEAK"))
timedOut = True
pass
return True
if len(A)<=2 and not timedOut:
#say("Wikipedia article "+topic+" not found.", more=False, speak=setting("SPEAK"))
retVal = False
else:
say(getResponse(inCmd), more=False, speak=setting("SPEAK"), PAUSE_SEND=True)
# get top 3 sentences on topic
top2=k.importantSentences(A, SEN_NUM=2, CHRON=True)
topStrs=[sen[0] for sen in top2]
strProcessed=processResponse("Let me tell you about \"#0#\": \n\t- #1# #2#", replacements=[topic, topStrs[0], topStrs[1]])
say(strProcessed, more=False, speak=setting("SPEAK"))
retVal = True
return retVal
if "word web" in inStr:
if len(matches[0]) != 1:
say("I was expecting only one term in \"\"'s.", more=False, speak=setting("SPEAK"))
return False
say(getResponse(inCmd), more=False, speak=setting("SPEAK"), PAUSE_SEND=True)
try:
A = k.learn(matches[0][0])
except TimedOutExc:
say("Unable to get data from Wikipedia.", more=False, speak=setting("SPEAK"))
pass
return True
except:
pass
return True
if len(A) <= 2:
say("Wikipedia article "+matches[0][0]+" not found.", more=False, speak=setting("SPEAK"))
return False
else:
k.wordWeb(A)
return True
if ("draw" in inStr) or ("paint" in inStr) or ("painting" in inStr):
if len(matches[0]) != 1:
say("I was expecting only one term.", more=False, speak=setting("SPEAK"))
return False
say(getResponse(inCmd), more=False, speak=setting("SPEAK"), PAUSE_SEND=True)
#print "word:"+qWords[0]
try:
k.paintImage(k.learn(matches[0][0]))
return True
except TimedOutExc:
say("Unable to get data from Wikipedia.", more=False, speak=setting("SPEAK"))
pass
return False
return False
