def get_model_response():
params = request.get_json()
_logger.info('request params: %s' % params)
try:
dialog_context = parse_dataset_param(params, param_name='context')
except KeyError as e:
return get_api_error_response(
'Malformed request, no "%s" param was found' % e.message, 400,
_logger)
except ValueError as e:
return get_api_error_response('Malformed request: %s' % e.message, 400,
_logger)
emotion = params.get('emotion', DEFAULT_CONDITION)
if emotion not in EMOTIONS_TYPES:
return get_api_error_response(
'Malformed request, emotion param "%s" is not in emotion list %s' %
(emotion, list(EMOTIONS_TYPES)), 400, _logger)
response = get_response(dialog_context, emotion)
if not response:
_logger.error('No response for context: %s; emotion "%s"' %
(dialog_context, emotion))
return jsonify({}), 200
_logger.info('Given response: "%s" for context: %s; emotion "%s"' %
(response, dialog_context, emotion))
return jsonify({'response': response}), 200
def get_model_response():
params = request.get_json()
_logger.info('request params: %s' % params)
try:
dialog_context = parse_dataset_param(params, param_name='context')
except KeyError as e:
return get_api_error_response('Malformed request, no "%s" param was found' % e.message, 400, _logger)
except ValueError as e:
return get_api_error_response('Malformed request: %s' % e.message, 400, _logger)
emotion = params.get('emotion', DEFAULT_CONDITION)
if emotion not in EMOTIONS_TYPES:
return get_api_error_response('Malformed request, emotion param "%s" is not in emotion list %s' %
(emotion, list(EMOTIONS_TYPES)), 400, _logger)
response = get_response(dialog_context, emotion)
if not response:
_logger.error('No response for context: %s; emotion "%s"' % (dialog_context, emotion))
return jsonify({}), 200
_logger.info('Given response: "%s" for context: %s; emotion "%s"' % (response, dialog_context, emotion))
return jsonify({'response': response}), 200
def get_model_response():
params = request.get_json()
_logger.info('request params: {}'.format(params))
try:
dialog_context = parse_dataset_param(params, param_name='context')
except KeyError as e:
return get_api_error_response(
'Malformed request, no "{}" param was found'.format(e), 400,
_logger)
except ValueError as e:
return get_api_error_response('Malformed request: {}'.format(e), 400,
_logger)
emotion = params.get('emotion', DEFAULT_CONDITION)
if emotion not in EMOTIONS_TYPES:
return get_api_error_response(
'Malformed request, emotion param "{}" is not in emotion list {}'.
format(emotion, list(EMOTIONS_TYPES)), 400, _logger)
response = get_response(dialog_context, emotion)
_logger.info('Given response: "{}" for context: {}; emotion "{}"'.format(
response, dialog_context, emotion))
return jsonify({'response': response}), 200
async def on_message(message):
if (message.author.bot == True):
return
if message.content.startswith('-'):
context.append(str(message.content)[1:].strip())
response = get_response(context, DEFAULT_CONDITION)
context.append(response)
await client.send_typing(message.channel)
await asyncio.sleep(1)
await client.send_message(message.channel, response)
async def on_message(message):
if not (message.author == client.user
): #Check to ensure the bot does not respond to its own messages
if (client.user.mentioned_in(message)
or isinstance(message.channel, discord.abc.PrivateChannel)
): #Check if the bot is mentioned or if the message is in DMs
async with message.channel.typing(): #Show that the bot is typing
txtinput = message.content.replace(
"<@" + str(client.user.id) + ">", "").replace(
"<@!" + str(client.user.id) + ">", ""
) #Filter out the mention so the bot does not get confused
if (len(txtinput) > 220): #Spam protection
txt = "I am sorry, that is too long for me."
dicestr = re.search("Roll (\d{1,2})d(\d{1,3})",
message.content)
if (dicestr != None):
dice = [dicestr.group(1), dicestr.group(2)]
output = "I rolled "
for i in range(int(dice[0])):
output += str(random.randrange(1, int(dice[1]))) + ", "
txt = output
else:
blob = TextBlob(txtinput)
#lang = blob.detect_language()
lang = "en"
if (lang != "en"):
txtinput = str(blob.translate(from_lang=lang, to="en"))
_context.append(txtinput)
COND = await es.new_sentiment_analysis(
txtinput
) #Determine how to respond to the sentence emotionally
await client.change_presence(
activity=discord.Game(name='feeling ' + COND)
) #Display the bot's emotion as a status
txt = get_response(_context, COND) #Get a response!
response_blob = TextBlob(txt)
if (lang != "en"):
txt = str(
response_blob.translate(from_lang="en", to=lang))
bot_message = await message.channel.send(txt) #Fire away!
def get_model_response():
params = request.get_json()
_logger.info('request params: %s' % params)
try:
dialog_context = parse_dataset_param(params, param_name='context')
except KeyError as e:
return get_api_error_response(
'Malformed request, no "%s" param was found' % str(e), 400,
_logger)
except ValueError as e:
return get_api_error_response('Malformed request: %s' % str(e), 400,
_logger)
emotion = params.get('emotion', DEFAULT_CONDITION)
custom_chatbot = chatbots.get(emotion)
if emotion not in EMOTIONS_TYPES and not custom_chatbot:
return get_api_error_response(
'Malformed request, emotion param "%s" is not in emotion list %s' %
(emotion, list(EMOTIONS_TYPES)), 400, _logger)
if custom_chatbot:
try:
response = custom_chatbot.make_prediction(dialog_context[-1])[0]
except IndexError:
response = "I'm not sure."
else:
response = get_response(dialog_context, emotion)
if not response:
_logger.error('No response for context: %s; emotion "%s"' %
(dialog_context, emotion))
return jsonify({}), 200
_logger.info('Given response: "%s" for context: %s; emotion "%s"' %
(response, dialog_context, emotion))
return jsonify({'response': response}), 200
def handle_text_message(self, msg_text, msg):
self._context.append(msg_text.strip())
response = get_response(self._context, DEFAULT_CONDITION)
self._context.append(response)
self._send_text(response)
def handle_text_message(self, msg_text, msg):
self._context.append(msg_text.strip())
response = get_response(self._context, DEFAULT_CONDITION)
self._context.append(response)
self._send_text(response)