にゃーんBOT(@nya_n_)

β版です。
多分何もエラーがでなければβのままです。
後は定期ポストの語彙を増やすだけぐらいかな。
機能は
1.発言
2.リプライに反応
3.フォロワーの発言を収集してマルコフ連鎖して発言
のみです。
大した発言もしないですし、大した返しもしてくれません。
あ、後
4.猫で癒される
猫ってだけで癒されますね！！

今大したエラーがおきてます
直ったー…かな

ソース

application.py

#coding: utf-8
from flask import Flask
app = Flask(__name__)
app.debug = True

from google.appengine.ext import db
from google.appengine.api import urlfetch

from flask import redirect, url_for, request, render_template, abort, flash, get_flashed_messages
import tweepy
import random
from markov import markov , morph

CONSUMER_KEY = '自分で登録した値'
CONSUMER_SECRET = '上に同じ'
TOKEN_KEY = '上に同じ'
TOKEN_SECRET = '上に同じ'

class Contexts(db.Model):
    context = db.StringProperty()

class ReplyContexts(db.Model):
    context = db.StringProperty()

class LatestReplyId(db.Model):
    reply_id = db.IntegerProperty()

class MyModel(db.Model):
    updated = db.StringProperty()

@app.route('/post_form/')
def post_form(context=None):
    return render_template('form.html')

@app.route('/post_update/',methods=['GET','POST'])
def post_update():
    if request.method == 'POST':
        context = request.form['context']
        update(context)
        return redirect(url_for('post_form'))
    return 'Sample'

@app.route('/rnd_update/')
def rnd_update():
    query = Contexts.all()
    results = query.fetch(1000)
    result = results[random.randint(0,len(results)-1)]
    update(result.context)
    return result.context
    
@app.route('/insert_form/',methods=['GET','POST'])
def insert_form(context = None):
    if request.method == 'POST':
        context_str = request.form['context']
        cont = Contexts(context=context_str)
        db.put(cont)
    else:
        pass
    return render_template('insert_form.html')

def update(context = None,consumer_key = CONSUMER_KEY, \
    consumer_secret = CONSUMER_SECRET,token_key = TOKEN_KEY, token_secret = TOKEN_SECRET):
    if context != None:
        context = context.encode('utf-8')
        auth = tweepy.OAuthHandler(consumer_key,consumer_secret)
        auth.set_access_token(token_key,token_secret)
        api = tweepy.API(auth)
        api.update_status(context)
        return True
    return False

def get_API(consumer_key = CONSUMER_KEY,consumer_secret=CONSUMER_SECRET,\
    token_key = TOKEN_KEY,token_secret = TOKEN_SECRET):
    api = None
    auth = tweepy.OAuthHandler(consumer_key,consumer_secret)
    auth.set_access_token(token_key,token_secret)
    api = tweepy.API(auth)
    return api

@app.route('/markov/')
def twi_markov(context = None):
    api = get_API()
    timeline = api.friends_timeline(count=5)
    context = timeline[random.randint(0,len(timeline) -1 )].text
    for tweet in timeline:
        context = context + tweet.text
    context = markov(morph(sentence = context))
    context.replace('@',' ')
    update(context = context)
    return context
    
@app.route('/rnd_reply/')
def rnd_reply():
    api = get_API()
    query = ReplyContexts.all()
    db_reply_id = query.fetch(10).pop() 
    latest_reply_id = db_reply_id.reply_id
    timelines = api.friends_timeline(latest_reply_id)
    if len(timelines) > 0:
        for status in timelines:


    return None

# set the secret key.  keep this really secret:
app.secret_key = '自分で設定した値'

if __name__ == '__main__':
    app.run()

markov.py

# coding:utf-8

import urllib,urllib2
from BeautifulSoup import BeautifulSoup
import random

appid = "アプリケーションid"
pageurl = "http://jlp.yahooapis.jp/MAService/V1/parse"

def morph(sentence = None, appid=appid, results="ma", app_filter="1|2|3|4|5|6|7|8|9|10|11|12|13"):
    ret = {}
    sentence = urllib.quote_plus(sentence.encode('utf-8'))
    query = "%s?appid=%s&results=%s&filter=%s&sentence=%s" % (pageurl, appid, results, app_filter, sentence)
    #c = urlfetch.fetch(query,deadline=10)
    c = urllib2.urlopen(url=query)
    soup = BeautifulSoup(c.read())
    surfaces = []
    print soup
    for w in soup.ma_result.word_list:
        surfaces.append(w.surface.string)
    return surfaces

def get_important_word(sentence = None, appid=appid):
    #http://jlp.yahooapis.jp/KeyphraseService/V1/extract?appid=<あなたのアプリケーションID>&sentence=<対象のテキスト>
    sentence = urllib.quote_plus(sentence.encode('utf-8'))
    query = "http://jlp.yahooapis.jp/KeyphraseService/V1/extract?appid=%s&sentence=%s" % (appid,sentence)
    c = urllib2.urlopen(url=query)
    soup = BeautifulSoup(c.read())
    print soup.results

    results = soup.findAll('result')
    important_words = []
    return soup


def markov(word_list=None):
    MAXGEN = 15
    nonword = "\n"
    w1 = w2 = nonword
    markov = {}
    content = ""
    for word in word_list:
        if not markov.has_key((w1,w2)):
            markov[(w1,w2)] = []
        markov[(w1,w2)].append(word)
        w1,w2 = w2,word
    if not markov.has_key((w1,w2)):
        markov[(w1,w2)] = []

    markov[(w1,w2)].append(nonword)
    w1 = w2 = nonword
    for i in range(MAXGEN):
        suf = markov[(w1,w2)]
        r = random.randint(0,len(suf) - 1)
        t = suf[r]
        if t == nonword:
            break
        content = content + t
        w1,w2 = w2,t
    return content

if __name__=='__main__':
    sentence = u'隣の庭ではニワトリを二羽飼っている'
    #result = morph(sentence)
    result = get_important_word(sentence=sentence)

マルコフ連鎖の部分はこのサイト様を参考にさして頂きました http://d.hatena.ne.jp/pylet/20060501/markov