def main():
"""This task consists of one agent, model or MTurk worker, talking to an
MTurk worker to negotiate a deal.
"""
argparser = ParlaiParser(False, False)
argparser.add_parlai_data_path()
argparser.add_mturk_args()
argparser.add_argument('-min_t',
'--min_turns',
default=5,
type=int,
help='minimum number of turns')
argparser.add_argument('-mt',
'--max_turns',
default=10,
type=int,
help='maximal number of chat turns')
argparser.add_argument(
'-mx_rsp_time',
'--max_resp_time',
default=150,
type=int,
help='time limit for entering a dialog message',
)
argparser.add_argument(
'--ag_shutdown_time',
default=120,
type=int,
help='time limit for entering a dialog message',
)
argparser.add_argument(
'--persona-type',
default='both',
type=str,
choices=['both', 'self', 'other'],
help='Which personas to load from personachat',
)
opt = argparser.parse_args()
directory_path = os.path.dirname(os.path.abspath(__file__))
opt['task'] = os.path.basename(directory_path)
opt['extract_personas_path'] = os.path.join(opt['datapath'], opt['task'])
opt.update(task_config)
mturk_agent_ids = ['PERSON_1']
mturk_manager = MTurkManager(opt=opt, mturk_agent_ids=mturk_agent_ids)
mturk_manager.setup_server(task_directory_path=directory_path)
personas_generator = PersonasGenerator(opt)
opt['personas_generator'] = personas_generator
try:
mturk_manager.start_new_run()
mturk_manager.create_hits()
if not opt['is_sandbox']:
# ADD BLOCKED WORKERS HERE
blocked_worker_list = []
for w in blocked_worker_list:
mturk_manager.block_worker(
w,
'We found that you have unexpected behaviors in our '
'previous HITs. For more questions please email us.',
)
def run_onboard(worker):
pass
mturk_manager.set_onboard_function(onboard_function=run_onboard)
mturk_manager.ready_to_accept_workers()
def check_worker_eligibility(worker):
return True
def assign_worker_roles(workers):
for index, worker in enumerate(workers):
worker.id = mturk_agent_ids[index % len(mturk_agent_ids)]
def run_conversation(mturk_manager, opt, workers):
worker = workers[0]
world = RephrasePersonaWorld(opt, worker)
while not world.episode_done():
world.parley()
world.save_data()
world.shutdown()
world.review_work()
mturk_manager.start_task(
eligibility_function=check_worker_eligibility,
assign_role_function=assign_worker_roles,
task_function=run_conversation,
)
except BaseException:
raise
finally:
mturk_manager.expire_all_unassigned_hits()
mturk_manager.shutdown()
def main():
"""This task consists of one agent, model or MTurk worker, talking to an
MTurk worker to negotiate a deal.
"""
argparser = ParlaiParser(False, False)
argparser.add_parlai_data_path()
argparser.add_mturk_args()
argparser.add_argument('-min_t', '--min_turns', default=5, type=int,
help='minimum number of turns')
argparser.add_argument('-mt', '--max_turns', default=10, type=int,
help='maximal number of chat turns')
argparser.add_argument('-mx_rsp_time', '--max_resp_time', default=150,
type=int,
help='time limit for entering a dialog message')
argparser.add_argument('-mx_psn_time', '--max_persona_time', type=int,
default=300, help='time limit for turker'
'entering the persona')
argparser.add_argument('--ag_shutdown_time', default=120,
type=int,
help='time limit for entering a dialog message')
argparser.add_argument('-rp', '--range_persona', default='4,6',
help='sample range of number of persona sentences')
opt = argparser.parse_args()
opt['task'] = os.path.basename(os.path.dirname(os.path.abspath(__file__)))
if 'data_path' not in opt:
opt['data_path'] = os.getcwd() + '/data/' + opt['task']
opt.update(task_config)
mturk_agent_ids = ['PERSON_1']
mturk_manager = MTurkManager(
opt=opt,
mturk_agent_ids=mturk_agent_ids
)
mturk_manager.setup_server()
try:
mturk_manager.start_new_run()
mturk_manager.create_hits()
if not opt['is_sandbox']:
# ADD BLOCKED WORKERS HERE
blocked_worker_list = []
for w in blocked_worker_list:
mturk_manager.block_worker(w, 'We found that you have unexpected behaviors in our previous HITs. For more questions please email us.')
def run_onboard(worker):
pass
mturk_manager.set_onboard_function(onboard_function=run_onboard)
mturk_manager.ready_to_accept_workers()
def check_worker_eligibility(worker):
return True
def assign_worker_roles(workers):
for index, worker in enumerate(workers):
worker.id = mturk_agent_ids[index % len(mturk_agent_ids)]
def run_conversation(mturk_manager, opt, workers):
worker = workers[0]
world = PersonaProfileWorld(opt, worker)
while not world.episode_done():
world.parley()
world.save_data()
world.shutdown()
mturk_manager.start_task(
eligibility_function=check_worker_eligibility,
assign_role_function=assign_worker_roles,
task_function=run_conversation
)
except BaseException:
raise
finally:
mturk_manager.expire_all_unassigned_hits()
mturk_manager.shutdown()
def main():
"""This task consists of one agent, model or MTurk worker, talking to an
MTurk worker to negotiate a deal.
"""
argparser = ParlaiParser(False, False)
argparser.add_parlai_data_path()
argparser.add_mturk_args()
argparser.add_argument('-min_t',
'--min_turns',
default=5,
type=int,
help='minimum number of turns')
argparser.add_argument('-mt',
'--max_turns',
default=10,
type=int,
help='maximal number of chat turns')
argparser.add_argument(
'-mx_rsp_time',
'--max_resp_time',
default=150,
type=int,
help='time limit for entering a dialog message',
)
argparser.add_argument(
'-mx_psn_time',
'--max_persona_time',
type=int,
default=300,
help='time limit for turker'
'entering the persona',
)
argparser.add_argument(
'--ag_shutdown_time',
default=120,
type=int,
help='time limit for entering a dialog message',
)
argparser.add_argument(
'--persona-type',
default='both',
type=str,
choices=['both', 'self', 'other'],
help='Which personas to load from personachat',
)
argparser.add_argument('--revised',
default=False,
type='bool',
help='Whether to use revised personas')
argparser.add_argument('-rt',
'--range_turn',
default='5,7',
help='sample range of number of turns')
argparser.add_argument('--personas-path',
default=None,
help='specify path for personas data')
opt = argparser.parse_args()
directory_path = os.path.dirname(os.path.abspath(__file__))
opt['task'] = os.path.basename(directory_path)
if not opt.get('personas_path'):
opt['personas_path'] = (argparser.parlai_home +
'/parlai/mturk/personachat_chat/data')
opt.update(task_config)
opt['extract_personas_path'] = os.path.join(opt['datapath'],
'personachat_chat')
mturk_agent_ids = ['PERSON_1', 'PERSON_2']
mturk_manager = MTurkManager(opt=opt, mturk_agent_ids=mturk_agent_ids)
persona_generator = PersonasGenerator(opt)
mturk_manager.setup_server(task_directory_path=directory_path)
try:
mturk_manager.start_new_run()
mturk_manager.create_hits()
if not opt['is_sandbox']:
blocked_worker_list = []
for w in blocked_worker_list:
mturk_manager.block_worker(
w,
'We found that you have unexpected behaviors in our previous '
'HITs. For more questions please email us.',
)
def run_onboard(worker):
worker.persona_generator = persona_generator
world = PersonaProfileWorld(opt, worker)
world.parley()
world.shutdown()
mturk_manager.set_onboard_function(onboard_function=run_onboard)
mturk_manager.ready_to_accept_workers()
def check_worker_eligibility(worker):
return True
def assign_worker_roles(workers):
for index, worker in enumerate(workers):
worker.id = mturk_agent_ids[index % len(mturk_agent_ids)]
def run_conversation(mturk_manager, opt, workers):
agents = [workers[0], workers[1]]
conv_idx = mturk_manager.conversation_index
world = PersonaChatWorld(
opt=opt,
agents=agents,
range_turn=[int(s) for s in opt['range_turn'].split(',')],
max_turn=opt['max_turns'],
max_resp_time=opt['max_resp_time'],
world_tag='conversation t_{}'.format(conv_idx),
)
world.reset_random()
while not world.episode_done():
world.parley()
world.save_data()
world.shutdown()
world.review_work()
mturk_manager.start_task(
eligibility_function=check_worker_eligibility,
assign_role_function=assign_worker_roles,
task_function=run_conversation,
)
except BaseException:
raise
finally:
mturk_manager.expire_all_unassigned_hits()
mturk_manager.shutdown()
def main():
"""This task consists of an MTurk agent evaluating a chit-chat model. They
are asked to chat to the model adopting a specific persona. After their
conversation, they are asked to evaluate their partner on several metrics.
"""
argparser = ParlaiParser(False, add_model_args=True)
argparser.add_parlai_data_path()
argparser.add_mturk_args()
argparser.add_argument('-mt',
'--max-turns',
default=10,
type=int,
help='maximal number of chat turns')
argparser.add_argument('--max-resp-time',
default=180,
type=int,
help='time limit for entering a dialog message')
argparser.add_argument('--max-persona-time',
type=int,
default=300,
help='time limit for turker'
'entering the persona')
argparser.add_argument('--ag-shutdown-time',
default=120,
type=int,
help='time limit for entering a dialog message')
argparser.add_argument('--persona-type',
default='both',
type=str,
choices=['both', 'self', 'other'],
help='Which personas to load from personachat')
argparser.add_argument('--revised',
default=False,
type='bool',
help='Whether to use revised personas')
argparser.add_argument('-rt',
'--range-turn',
default='5,6',
help='sample range of number of turns')
argparser.add_argument('--auto-approve-delay',
type=int,
default=3600 * 24 * 1,
help='how long to wait for \
auto approval')
# ADD MODEL ARGS HERE (KVMEMNN ADDED AS AN EXAMPLE)
argparser.set_defaults(
model='projects.personachat.kvmemnn.kvmemnn:Kvmemnn',
model_file='models:convai2/kvmemnn/model',
)
opt = argparser.parse_args()
# add additional model args
opt['no_cuda'] = True
opt['override'] = ['interactive_mode']
opt['interactive_mode'] = True
bot = create_agent(opt)
shared_bot_params = bot.share()
opt['task'] = os.path.basename(os.path.dirname(os.path.abspath(__file__)))
if 'data_path' not in opt:
opt['data_path'] = os.getcwd() + '/data/' + opt['task']
opt.update(task_config)
mturk_agent_ids = ['PERSON_1']
mturk_manager = MTurkManager(opt=opt, mturk_agent_ids=mturk_agent_ids)
persona_generator = PersonasGenerator(opt)
mturk_manager.setup_server()
try:
mturk_manager.start_new_run()
mturk_manager.create_hits()
if not opt['is_sandbox']:
# ADD BLOCKED WORKERS HERE
blocked_worker_list = []
for w in blocked_worker_list:
mturk_manager.block_worker(
w, 'We found that you have unexpected behaviors in our \
previous HITs. For more questions please email us.')
def run_onboard(worker):
worker.persona_generator = persona_generator
world = PersonaProfileWorld(opt, worker)
world.parley()
world.shutdown()
mturk_manager.set_onboard_function(onboard_function=run_onboard)
mturk_manager.ready_to_accept_workers()
def check_worker_eligibility(worker):
return True
def assign_worker_roles(workers):
for index, worker in enumerate(workers):
worker.id = mturk_agent_ids[index % len(mturk_agent_ids)]
def run_conversation(mturk_manager, opt, workers):
agents = workers[0]
conv_idx = mturk_manager.conversation_index
world = Convai2EvalWorld(
opt=opt,
agents=[agents],
range_turn=[int(s) for s in opt['range_turn'].split(',')],
max_turn=opt['max_turns'],
max_resp_time=opt['max_resp_time'],
model_agent_opt=shared_bot_params,
world_tag='conversation t_{}'.format(conv_idx),
agent_timeout_shutdown=opt['ag_shutdown_time'],
)
world.reset_random()
while not world.episode_done():
world.parley()
world.save_data()
world.shutdown()
world.review_work()
mturk_manager.start_task(eligibility_function=check_worker_eligibility,
assign_role_function=assign_worker_roles,
task_function=run_conversation)
except BaseException:
raise
finally:
mturk_manager.expire_all_unassigned_hits()
mturk_manager.shutdown()
