def dev():
import core.markovchain as mc
mcW = mc.MarkovChain()
sm = sentence.SentenceMaker(mcW)
ss = sentences_from_thesaurus(["cat", "anger", "sorry", "cat"], mcW)
for s in ss:
sent = sm.polish_sentence(s)
print(" " + sm.to_string(sent))
def dev():
import knowledge.names as names
mcW = mc.MarkovChain()
nm = names.NameMaker()
speakers = [nm.random_person() for i in range(1, 4)]
dm = dialogue_maker([n['name'] for n in speakers], [n['pronoun'] for n in speakers], mcW)
dlg = dm.make_dialogue(["dog", "run", "spot"])
print(dlg)
def dev():
mcW = mc.MarkovChain()
w2vec = w2v.WordVectors()
seeds = w2vec.path("swim", 20)
print(seeds)
generator = sentence.SentenceMaker(mcW)
for sd in seeds:
sen = generator.generate_sentence_tokens([sd])
sen = generator.polish_sentence(sen)
print(" " + sentence.SentenceMaker.to_string(sen))
print('')
nm = names.NameMaker()
speakers = [nm.random_person() for i in range(1, 4)]
dm = dialogue.dialogue_maker([n['name'] for n in speakers],
[n['pronoun'] for n in speakers], mcW, seeds)
dlg = dm.make_dialogue()
for s in dlg:
print(" " + sentence.SentenceMaker.to_string(s))
story_grammar.make_story(generator)
def dev():
print("hello!")
fileids = range(112, 200) # [102, 103, 105, 107,108, 109, 110, 111]
global mcW_store
mcW_store = mc.MarkovChain()
global ti
ti = text_importer.TextImporter()
# print(store.random_entry())
# print("Serial test...")
# start_time = time.perf_counter()
# s3_to_mc(fileids[0])
# elapsed_time = time.perf_counter() - start_time
# s_elapsed_time=elapsed_time
# print(s_elapsed_time)
# print("...serial done!")
start_time = time.perf_counter()
mass_import(fileids)
elapsed_time = time.perf_counter() - start_time
p_elapsed_time = elapsed_time
print(p_elapsed_time)
print("...parallel done! {} files".format(len(fileids)))
import argparse
import core.sentence as sentence
import core.markovchain as mc
import core.paragraphs as paras
import nlp.story_grammar as story_grammar
import knowledge.names as names
import core.dialogue as dialogue
mcW = mc.MarkovChain()
generator = sentence.SentenceMaker(mcW)
def make_seeds(seeds, max=5):
if seeds is None:
seeds = generator.generate_sentence_tokens(["the"]) # Make a random sentence of seeds
seeds = seeds[0:max]
return seeds
def make_sentences(n, seeds=None):
seeds = make_seeds(seeds)
# if seeds is None:
# seeds = generator.generate_sentence_tokens(["the"]) # Make a random sentence of seeds
if isinstance(seeds, str):
seeds = seeds.split()
p = paras.seq_to_para(seeds[0:n], mcW)
for sent in p:
print(generator.to_string(generator.polish_sentence(sent)))
def make_story():