def edit_message(response, chat, message, page):
dm.save_page(chat, message, page)
bot.edit_message_text(response,
chat,
message,
reply_markup=get_markup(),
parse_mode='Markdown')
def pipeline(message):
# NER
message_counter = 2
slots = nlu.NER.NamedEntityRecognition(message.text)
if message.chat.id in Slots:
for slot in slots:
if slot in Slots[message.chat.id]:
Slots[message.chat.id][slot] = set.union(slots[slot], Slots[message.chat.id][slot])
else:
Slots[message.chat.id][slot] = slots[slot]
else:
Slots[message.chat.id] = slots
logger.info("###SLOTS###")
logger.info(Slots)
# Clarifyings
if len(Slots[message.chat.id]) == 0:
return dm.States.R_CLARIFY_ALL.value, message_counter
if len(Slots[message.chat.id]) == 1:
if 'ACTOR' in Slots[message.chat.id]:
return dm.States.R_CLARIFY_GENRE.value, message_counter
# Processing Plot
keywords_id = set()
if 'PLOT' in Slots[message.chat.id]:
n_matches = 5
plot = " ".join(Slots[message.chat.id]['PLOT'])
df = nlu.MoviePlot.plot2movie(plot, n_matches=n_matches)
max_page = n_matches if df.shape[0] >= n_matches else df.shape[0]
if max_page != 0:
films = dm.api_movie(config.DB_API_TOKEN, df['tmdbId'].iloc[:max_page].values)
dm.save_request(message.chat.id, message.message_id + message_counter, films)
dm.save_page(message.chat.id, message.message_id + message_counter, page=1)
return dm.States.R_OK.value, message_counter
else:
for word in plot.split()[:5]:
if add_keywords(message.chat.id, word):
keywords_id = Slots[message.chat.id]['KEYWORDS']
# If plot gives no result
actors_id = []; genres_id = []; director_id = []; year=None
if 'GENRE' in Slots[message.chat.id]:
for genre in Slots[message.chat.id]['GENRE']:
closest = dm.find_levenshtein_closest(genre, list(dm.ApiDicts.genre_to_id.keys()))
if closest == False:
if add_keywords(message.chat.id, genre):
keywords_id = Slots[message.chat.id]['KEYWORDS']
else:
genres_id.append(dm.ApiDicts.genre_to_id[closest])
if len(genres_id) == 0 and len(list(keywords_id)) == 0:
return dm.States.R_CLARIFY_GENRE.value, message_counter
if 'ACTOR' in Slots[message.chat.id]:
for actor in Slots[message.chat.id]['ACTOR'].copy():
if actor.lower() in dm.ApiDicts.person_to_id:
actors_id.append(dm.ApiDicts.person_to_id[actor.lower()][0])
else:
message_counter += 1
bot.send_message(message.chat.id, "I don’t know who is " + actor + ". Please, check spelling.")
Slots[message.chat.id]['ACTOR'].remove(actor)
if len(actors_id) == 0:
return dm.States.R_CLARIFY_ACTOR.value, message_counter
if 'DIRECTOR' in Slots[message.chat.id]:
for director in Slots[message.chat.id]['DIRECTOR'].copy():
if director.lower() in dm.ApiDicts.person_to_id:
director_id.append(dm.ApiDicts.person_to_id[director.lower()][0])
else:
message_counter += 1
bot.send_message(message.chat.id, "I don’t know who is " + director + ". Please, check spelling.")
Slots[message.chat.id]['DIRECTOR'].remove(director)
if 'YEAR' in Slots[message.chat.id]:
year = str(nlu.extract_year(Slots[message.chat.id]['YEAR'].pop()))
print("parsed year: ", year)
if len(genres_id + actors_id + director_id + list(keywords_id)) != 0 or year != None:
print("Call API with genres=", genres_id, " and actors=", actors_id, " and directors=", director_id)
films = dm.api_discover(config.DB_API_TOKEN, genres=genres_id, actors=actors_id, crew=director_id, keywords=keywords_id, year=year)
if json.loads(films)["total_results"] == 0:
return dm.States.R_NONE.value, message_counter
else:
dm.save_request(message.chat.id, message.message_id + message_counter, films)
dm.save_page(message.chat.id, message.message_id + message_counter, page=1)
return dm.States.R_OK.value, message_counter
else:
return dm.States.R_NONE.value, message_counter