def setup_args(parser=None):
if parser is None:
parser = ParlaiParser(True, True,
'Like interactive, but adds a safety filter')
parser.add_argument('-d', '--display-examples', type='bool', default=False)
parser.add_argument(
'--display-prettify',
type='bool',
default=False,
help='Set to use a prettytable when displaying '
'examples with text candidates',
)
parser.add_argument(
'--display-add-fields',
type=str,
default='',
help=
'Display these fields when verbose is off (e.g., "--display-add-fields label_candidates,beam_texts")',
)
parser.add_argument(
'-it',
'--interactive-task',
type='bool',
default=True,
help='Create interactive version of task',
)
parser.set_defaults(interactive_mode=True, task='interactive')
SafeLocalHumanAgent.add_cmdline_args(parser, partial_opt=None)
return parser
def setup_args(parser=None):
if parser is None:
parser = ParlaiParser(True, True, 'Interactive chat with a model')
parser.add_argument('-d', '--display-examples', type='bool', default=False)
parser.add_argument(
'--display-prettify',
type='bool',
default=False,
help='Set to use a prettytable when displaying '
'examples with text candidates',
)
parser.add_argument(
'--display-ignore-fields',
type=str,
default='label_candidates,text_candidates',
help='Do not display these fields',
)
parser.add_argument(
'-it',
'--interactive-task',
type='bool',
default=True,
help='Create interactive version of task',
)
parser.set_defaults(interactive_mode=True, task='interactive')
SafeLocalHumanAgent.add_cmdline_args(parser)
return parser
def interactive(opt, print_parser=None):
if print_parser is not None:
if print_parser is True and isinstance(opt, ParlaiParser):
print_parser = opt
elif print_parser is False:
print_parser = None
if isinstance(opt, ParlaiParser):
print(
'[ Deprecated Warning: interactive should be passed opt not Parser ]'
)
opt = opt.parse_args()
# Create model and assign it to the specified task
agent = create_agent(opt, requireModelExists=True)
if print_parser:
# Show arguments after loading model
print_parser.opt = agent.opt
print_parser.print_args()
human_agent = SafeLocalHumanAgent(opt)
world = create_task(opt, [human_agent, agent])
# Show some example dialogs:
while True:
world.parley()
if opt.get('display_examples'):
print("---")
print(world.display())
if world.epoch_done():
print("EPOCH DONE")
break
def safe_interactive(opt, print_parser=None):
if print_parser is not None:
if print_parser is True and isinstance(opt, ParlaiParser):
print_parser = opt
elif print_parser is False:
print_parser = None
if isinstance(opt, ParlaiParser):
print(
'[ Deprecated Warning: interactive should be passed opt not Parser ]'
)
opt = opt.parse_args()
# Create model and assign it to the specified task
agent = create_agent(opt, requireModelExists=True)
if print_parser:
# Show arguments after loading model
print_parser.opt = agent.opt
print_parser.print_args()
human_agent = SafeLocalHumanAgent(opt)
world = create_task(opt, [human_agent, agent])
# Interact until episode done
while True:
world.parley()
bot_act = world.get_acts()[-1]
if 'bot_offensive' in bot_act and bot_act['bot_offensive']:
agent.reset()
if opt.get('display_examples'):
print('---')
print(world.display())
if world.epoch_done():
print('EPOCH DONE')
break
def setup_agent():
random.seed(42)
parser = safe_interactive.setup_args()
parser.prog = ''
#parsed = parser.parse_args(print_args=False)
parsed = {
'init_opt': None,
'show_advanced_args': False,
'task': 'blended_skill_talk',
'download_path': '/home/ubuntu/ParlAI/downloads',
'datatype': 'train',
'image_mode': 'raw',
'numthreads': 1,
'hide_labels': False,
'multitask_weights': [1],
'batchsize': 1,
'dynamic_batching': None,
'datapath': '/home/ubuntu/ParlAI/data',
'model': 'blender_90M',
'model_file':
'/home/ubuntu/ParlAI/data/models/blender/blender_90M/model',
'init_model': None,
'dict_class': None,
'display_examples': False,
'display_prettify': False,
'display_ignore_fields': 'label_candidates,text_candidates',
'interactive_task': True,
'safety': 'all',
'local_human_candidates_file': None,
'single_turn': False,
'image_size': 256,
'image_cropsize': 224,
'interactive_mode': True,
'parlai_home': '/home/ubuntu/ParlAI',
'override': {},
'starttime': 'May08_22-10',
'display_partner_persona': False
}
parsed.update({'model': 'blender_90M'})
parsed.update({'model_file': 'zoo:blender/blender_90M/model'})
parsed.update({'task': 'blended_skill_talk'})
parsed.update({'display_partner_persona': False})
# can do all the instructions in the function. issue is its interactive
agent = create_agent(parsed, requireModelExists=True)
if parser:
# Show arguments after loading model
parser.opt = agent.opt
human_agent = SafeLocalHumanAgent(parsed)
world = create_task(parsed, [human_agent, agent])
return world
def safe_interactive_custom(opt, print_parser=None):
if print_parser is not None:
if print_parser is True and isinstance(opt, ParlaiParser):
print_parser = opt
elif print_parser is False:
print_parser = None
if isinstance(opt, ParlaiParser):
logging.error('interactive should be passed opt not Parser')
opt = opt.parse_args()
# Create model and assign it to the specified task
agent = create_agent(opt, requireModelExists=True)
if print_parser:
# Show arguments after loading model
print_parser.opt = agent.opt
print_parser.print_args()
human_agent = SafeLocalHumanAgent(opt)
world = create_task(opt, [human_agent, agent])
return world
def setup_interactive(self):
"""
Build and parse CLI opts.
"""
self.SHARED['opt'] = self.opt
self.SHARED['opt']['task'] = 'parlai.agents.local_human.local_human:LocalHumanAgent'
# Create model and assign it to the specified task
#import pdb; pdb.set_trace()
if 'models' in self.opt:
model_params = {}
for model in self.opt['models']:
model_opt = self.opt['models'][model]
agent = create_agent(model_opt, requireModelExists=True)
else:
agent = create_agent(self.opt, requireModelExists=True)
human_agent = SafeLocalHumanAgent(self.opt)
self.SHARED['agent'] = agent
self.SHARED['world'] = create_task(self.SHARED.get('opt'), [human_agent, self.SHARED['agent']])
def safe_interactive(opt):
if isinstance(opt, ParlaiParser):
logging.error('interactive should be passed opt not Parser')
opt = opt.parse_args()
# Create model and assign it to the specified task
agent = create_agent(opt, requireModelExists=True)
agent.opt.log()
human_agent = SafeLocalHumanAgent(opt)
world = create_task(opt, [human_agent, agent])
# Interact until episode done
while True:
world.parley()
bot_act = world.get_acts()[-1]
if 'bot_offensive' in bot_act and bot_act['bot_offensive']:
agent.reset()
if opt.get('display_examples'):
print('---')
print(world.display())
if world.epoch_done():
logging.info('epoch done')
break
def safe_interactive(opt, print_parser=None):
if print_parser is not None:
if print_parser is True and isinstance(opt, ParlaiParser):
print_parser = opt
elif print_parser is False:
print_parser = None
if isinstance(opt, ParlaiParser):
logging.error('interactive should be passed opt not Parser')
opt = opt.parse_args()
# Create model and assign it to the specified task
agent = create_agent(opt, requireModelExists=True)
if print_parser:
# Show arguments after loading model
print_parser.opt = agent.opt
print_parser.print_args()
human_agent = SafeLocalHumanAgent(opt)
world = create_task(opt, [human_agent, agent])
# Interact until episode done
# while True:
# world.parley()
# bot_act = world.get_acts()[-1]
# if 'bot_offensive' in bot_act and bot_act['bot_offensive']:
# agent.reset()
#
# if opt.get('display_examples'):
# print('---')
# print(world.display())
# if world.epoch_done():
# logging.info('epoch done')
# break
if not opt.get('chat_script'):
'''for chateval script evaluation'''
# Interact until episode done
while True:
world.parley()
bot_act = world.get_acts()[-1]
if 'bot_offensive' in bot_act and bot_act['bot_offensive']:
agent.reset()
if opt.get('display_examples'):
print('---')
print(world.display())
if world.epoch_done():
logging.info('epoch done')
break
# else:
elif opt.get('chat_script') and opt.get('include_personas'):
while True:
# world.parley_script(opt.get('script_input_path'), opt.get('script_output_path'), opt.get('model-file'))
# turn_available = [0, 2, 3]
world.parley_persona_script(opt.get('script_input_path'),
opt.get('script_output_path'),
opt.get('model_file'),
opt.get('chateval_multi'),
opt.get('chateval_multi_num'))
bot_act = world.get_acts()[-1]
if 'bot_offensive' in bot_act and bot_act['bot_offensive']:
agent.reset()
if opt.get('display_examples'):
print("---")
print(world.display())
if world.epoch_done():
logging.info('epoch done')
break
else:
while True:
# world.parley_script(opt.get('script_input_path'), opt.get('script_output_path'), opt.get('model-file'))
# turn_available = [0, 2, 3]
world.parley_script(opt.get('script_input_path'),
opt.get('script_output_path'),
opt.get('model_file'),
opt.get('chateval_multi'),
opt.get('chateval_multi_num'))
bot_act = world.get_acts()[-1]
if 'bot_offensive' in bot_act and bot_act['bot_offensive']:
agent.reset()
if opt.get('display_examples'):
print("---")
print(world.display())
if world.epoch_done():
logging.info('epoch done')
break
def setup_args(parser=None):
if parser is None:
parser = ParlaiParser(True, True, 'Interactive chat with a model')
parser.add_argument('-d', '--display-examples', type='bool', default=False)
parser.add_argument(
'--display-prettify',
type='bool',
default=False,
help='Set to use a prettytable when displaying '
'examples with text candidates',
)
parser.add_argument(
'--display-ignore-fields',
type=str,
default='label_candidates,text_candidates',
help='Do not display these fields',
)
parser.add_argument(
'-it',
'--interactive-task',
type='bool',
default=True,
help='Create interactive version of task',
)
parser.add_argument(
'-sc',
'--script-chateval',
type='bool',
default=False,
dest='chat_script',
help='Chateval script read file'
'True: chateval evaluation, False: single-turn conversation with agent(original model)',
)
parser.add_argument(
'-scip',
'--chateval-input-path',
type=str,
default=None,
dest='script_input_path',
help='Chateval script input path',
)
parser.add_argument(
'-scop',
'--chateval-output-path',
type=str,
default=None,
dest='script_output_path',
help='Chateval result output path',
)
parser.add_argument(
'--chateval-multi-num',
type=int,
default=0,
dest='chateval_multi_num',
help='True is chateval multiturn setting, turn coverage count.',
)
parser.add_argument(
'--chateval-multi',
type='bool',
default=False,
hidden=True,
dest='chateval_multi',
help='True is chateval multiturn setting, False just single turn.',
)
parser.set_defaults(interactive_mode=True, task='interactive')
SafeLocalHumanAgent.add_cmdline_args(parser)
return parser