pip install mecab

pip install mecab-python3

<?php
function mecab_tw_like($txt="",$connection=Null){
    if(!$txt)return false;
    if(!is_object($connection))return false;
    $cmd = "echo "$txt" | mecab";
    exec($cmd, $opt, $return_ver);
    //var_dump($opt);
    foreach($opt as $key=>$val){
        $r = explode("t",$val);
        if(preg_match("/名詞/",$r[1])){
            $statuses = $connection->get(
                'search/tweets',
                array(
                    'q'                 => $r[0],
                    'count'             => '3',
                    'lang'              => 'ja',
                    'locale'            => 'ja',
                    'result_type'       => 'recent',
                    'include_entities'  => 'false'
                )
            );
            if(is_array($statuses->statuses) and $statuses->statuses){
                foreach( $statuses->statuses as $tweet ){
                    $id = $tweet->id;
                    $result = $connection->post(
                        'favorites/create',
                        array(
                            'id' => $id
                        )
                    );
                }
            }
        }
    }
}

#!/usr/local/bin/python3
# coding:utf-8
import os
import sys
import MeCab
import gensim
import markovify
import unicodedata
model = gensim.models.KeyedVectors.load_word2vec_format('/var/www/html/model.vec', binary=False)
f = open('merosu.txt')
tagger = MeCab.Tagger("-Owakati")
tagger.parse('')
text0 = tagger.parse(f.read())
text1 = text0
text0 = text0.replace('\n','')
text0 = text0.replace('\r','')
text1x = text0.split(" ")
text2 = []
try:
    for item in text1x:
        if item.strip():
            results  = model.most_similar(positive=[item],topn=2)
            #"print(results)
            for val1 in results:
                text2.append(val1[0] + "\n")
#
    # print (text1)
    # print (" ".join(text2))
    model_a = markovify.Text(text1 + "\n")
    print(str(model_a.make_sentence()).replace(' ',''))
    model_b = markovify.Text(" ".join(text2))
    print(str(model_b.make_sentence()).replace(' ',''))
    model_combo = markovify.combine([model_a, model_b], [1, 1])
    print(str(model_combo.make_sentence()).replace(' ',''))
except Exception as e:
    print("動作エラー", e.args)
    pass