def compose_linkto_with_connection_phrase(skills,
human_attributes,
recent_active_skills=None,
from_skill=None):
from_skill = "" if from_skill is None else from_skill
linkto_dict = link_to(skills, human_attributes, recent_active_skills)
connection = get_prelinkto_connection(
from_skill, linkto_dict["skill"],
human_attributes.get("prelinkto_connections", []))
if not connection:
connection = get_prelinkto_topic_connection(
linkto_dict["skill"],
human_attributes.get("prelinkto_connections", []))
if not connection:
# not found prelinkto connection phrase AND not found prelinkto topic phrase
connection = get_not_used_template(
human_attributes.get("prelinkto_connections", []),
COMPLETELY_CHANGING_THE_SUBJECT_PHRASES)
result = f"{connection} {linkto_dict['phrase']}"
else:
# we have prelinkto connection phrase OR prelinkto topic phrase
change_topic = choice(CHANGE_TOPIC_SUBJECT).replace(
"SUBJECT", LIST_OF_SCRIPTED_TOPICS.get(linkto_dict["skill"], "it"))
result = f"{choice(BY_THE_WAY)} {connection} {change_topic} {linkto_dict['phrase']}"
return {
"phrase": result,
"skill": linkto_dict["skill"],
"connection_phrase": connection
}
def get_not_used_and_save_reaction_to_new_mentioned_person(vars):
shared_memory = state_utils.get_shared_memory(vars)
last_reactions_to_new_person = shared_memory.get(
"last_reactions_to_new_person", [])
reaction = common_utils.get_not_used_template(
used_templates=last_reactions_to_new_person,
all_templates=this_gossip.OPINION_TO_USER_MENTIONING_SOMEONE_NEW)
used_reacts = last_reactions_to_new_person + [reaction]
state_utils.save_to_shared_memory(
vars, last_reactions_to_new_person=used_reacts[-2:])
return reaction
def get_not_used_and_save_sentiment_acknowledgement(vars):
sentiment = state_utils.get_human_sentiment(vars)
if is_yes_vars(vars) or is_no_vars(vars):
sentiment = "neutral"
shared_memory = state_utils.get_shared_memory(vars)
last_acknowledgements = shared_memory.get("last_acknowledgements", [])
ack = common_utils.get_not_used_template(
used_templates=last_acknowledgements,
all_templates=GENERAL_ACKNOWLEDGEMENTS[sentiment])
used_acks = last_acknowledgements + [ack]
state_utils.save_to_shared_memory(vars,
last_acknowledgements=used_acks[-2:])
return ack
def get_not_used_and_save_generic_response(proposed_sf, vars):
logger.info(
f"Getting not yet used generic response for proposed speech function {proposed_sf}..."
)
shared_memory = state_utils.get_shared_memory(vars)
last_responses = shared_memory.get(proposed_sf + "_last_responses", [])
resp = common_utils.get_not_used_template(
used_templates=last_responses,
all_templates=current_templates.
GENERIC_REACTION_TO_USER_SPEECH_FUNCTION[proposed_sf],
)
used_resp = last_responses + [resp]
state_utils.save_to_shared_memory(vars, last_responses=used_resp[-2:])
return resp
def recommend_movie_of_genre(genre, discussed_movie_ids=None):
discussed_movie_ids = discussed_movie_ids if discussed_movie_ids is not None else []
# let's convert genre from `criminal` to `Crime` (standard IMDb genre)
for capitalized_genre in GENRES:
if genre.lower() in GENRES[capitalized_genre]:
genre = capitalized_genre
# randomly pick up not discussed movie
if RECOMMENDATIONS.get(genre, []):
# because in RECOMMENDATIONS file imdb ids are started from tt, but in our case we store only digits
available_ids = [pair[0][2:] for pair in RECOMMENDATIONS[genre]]
return get_not_used_template(discussed_movie_ids,
available_ids,
any_if_no_available=False)
return ""
def get_not_used_and_save_sentiment_acknowledgement(ctx: Context,
actor: Actor,
sentiment=None):
if sentiment is None:
sentiment = int_ctx.get_human_sentiment(ctx, actor)
if is_yes_vars(ctx, actor) or is_no_vars(ctx, actor):
sentiment = "neutral"
shared_memory = int_ctx.get_shared_memory(ctx, actor)
last_acknowledgements = shared_memory.get("last_acknowledgements", [])
ack = common_utils.get_not_used_template(
used_templates=last_acknowledgements,
all_templates=GENERAL_ACKNOWLEDGEMENTS[sentiment])
used_acks = last_acknowledgements + [ack]
int_ctx.save_to_shared_memory(ctx,
actor,
last_acknowledgements=used_acks[-2:])
return ack
def get_prelinkto_topic_connection(to_skill, used_templates):
if to_skill in PRELINKTO_TOPIC_PHRASES:
return get_not_used_template(used_templates,
PRELINKTO_TOPIC_PHRASES[to_skill])
return ""
def get_prelinkto_connection(from_skill, to_skill, used_templates):
skill_pair = sorted([from_skill, to_skill])
for el in PRELINKTO_CONNECTION_PHRASES:
if el.get("skill_pair") == skill_pair and el.get("phrases"):
return get_not_used_template(used_templates, el["phrases"])
return ""
