def get_bot_response():
userText = request.args.get('msg')
english_bot = ChatBot(
"Chatterbot",
storage_adapter="chatterbot.storage.SQLStorageAdapter",
preprocessors=[
'chatterbot.preprocessors.clean_whitespace',
'chatterbot.preprocessors.unescape_html',
'chatterbot.preprocessors.convert_to_ascii'
],
silence_performance_warning=True,
response_selection_method=get_most_frequent_response,
read_only=True,
logic_adapters=[{
'import_path': 'chatterbot.logic.BestMatch',
'default_response': 'I am sorry, but I do not understand.',
'maximum_similarity_threshold': 0.95
}])
english_bot.read_only = True
return str(english_bot.get_response(userText))
"ChatBot",
logic_adapters=[{
'import_path': 'chatterbot.logic.BestMatch'
}, {
'import_path': 'chatterbot.logic.LowConfidenceAdapter',
'threshold': confidenceLevel,
'default_response': 'IDKresponse'
}],
response_selection_method=
get_random_response, #Comment this out if you want best response
input_adapter="chatterbot.input.VariableInputTypeAdapter",
output_adapter="chatterbot.output.OutputAdapter",
storage_adapter="chatterbot.storage.SQLStorageAdapter",
database="botData.sqlite3")
bot.read_only = True #Comment this out if you want the bot to learn based on experience
print("Bot Learn Read Only:" + str(bot.read_only))
#You can comment these out for production later since you won't be training everytime:
#bot.set_trainer(ChatterBotCorpusTrainer)
#bot.train("data/trainingdata.yml")
def tryGoogle(myQuery):
#print("<br>Try this from my friend Google: <a target='_blank' href='" + j + "'>" + query + "</a>")
return "<br><br>You can try this from my friend Google: <a target='_blank' href='https://www.google.com/search?q=" + myQuery + "'>" + myQuery + "</a>"
@application.route("/")
def home():
return render_template("index.html",
"import_path": "chatterbot.logic.BestMatch",
#"statement_comparison_function": "chatterbot.comparisons.JaccardSimilarity",
#"response_selection_method": "chatterbot.response_selection.get_first_response"
},
{
'import_path':
'chatterbot.logic.LowConfidenceAdapter',
'threshold':
0.1, #0.6 originally 0.75 not bad
'default_response':
"sorry i didn't get you. Did you or didn't you go anywhere this chirstmas?"
}
],
)
chatbot.read_only = True
#chatbot2 first time
chatbot2 = ChatBot(
"first time",
storage_adapter="chatterbot.storage.MongoDatabaseAdapter", # 使用mongo存储数据
database="2dbn",
database_uri="mongodb://127.0.0.1:27017/",
logic_adapters=[
{
"import_path": "chatterbot.logic.BestMatch",
#"statement_comparison_function": "chatterbot.comparisons.JaccardSimilarity",
#"response_selection_method": "chatterbot.response_selection.get_first_response"
},
{
'import_path':
from chatterbot import ChatBot
from chatterbot.trainers import ChatterBotCorpusTrainer
# Uncomment the following lines to enable verbose logging
import logging
# logging.basicConfig(level=logging.INFO)
logging.basicConfig(level=logging.DEBUG)
bot = ChatBot(
"NoteBot",
storage_adapter="chatterbot.storage.SQLStorageAdapter",
database_uri="sqlite:///2003database.db",
logic_adapters=[
{
'import_path': 'chatterbot.logic.BestMatch'
},
{
'import_path': 'chatterbot.logic.LowConfidenceAdapter',
'threshold': 0.25,
'default_response': 'What?'
},
],
input_adapter="chatterbot.input.VariableInputTypeAdapter",
output_adapter="chatterbot.output.OutputAdapter",
)
bot.set_trainer(ChatterBotCorpusTrainer)
bot.train("corpus.out_2003")
bot.read_only = True
print("Train Complete")
'import_path': 'acronym_logic_adapter.AcronymLogicAdapter'
},
{
'import_path': 'greeting_logic_adapter.GreetingLogicAdapter'
},
{
'import_path': 'chatterbot.logic.LowConfidenceAdapter',
'threshold': 0.75,
'default_response': 'Acronym not found'
}],
trainer='chatterbot.trainers.ChatterBotCorpusTrainer'
)
bot.train('data/acronyms/acronyms.yml')
debug("chatterbot is running ...") #Changement type de training de corpus vers listrainer
bot.read_only = True #desactivation d'apprentissage automatique
@app.route('/message',methods=['POST'])
def post_message():
request_response = request.get_json(force=True,silent=True)
content = request_response['content'] #message from user
print('session ',bot.default_session.id_string)
response_dict = {'message': bot.get_response(content).text }
return jsonify(response_dict)
@app.route('/message',methods=['GET'])
def get_message():
response_dict = {'message': bot.get_response('ITG').text }
response_json = jsonify(response_dict)
print(type(response_json))
## Initialize ChatterBot
bot = ChatBot(
"ChatBot",
logic_adapters=[{
'import_path': 'chatterbot.logic.BestMatch'
}, {
'import_path': 'chatterbot.logic.LowConfidenceAdapter',
'threshold': confidenceLevel,
'default_response': 'IDKresponse'
}],
response_selection_method=
get_random_response, #Art der Anwortauswahl -> random
storage_adapter="chatterbot.storage.SQLStorageAdapter",
database=currentPath + "/database/botData.sqlite3")
bot.read_only = True #Comment out um den Bot basierend auf Erfahrungen lernen zu lassen.
logging.info("Bot Learn Read Only:" + str(bot.read_only))
# Diesen Teil nach Deployment ausgrauen, um dauerhaftes Lernen zu vermeiden
bot.set_trainer(ChatterBotCorpusTrainer)
bot.train("chatterbot.corpus.english.greetings",
"chatterbot.corpus.english.conversations",
currentPath + "/data/dialogues.yml")
# bot.storage.drop()
## Google fallback if response == IDKresponse
def tryGoogle(myQuery):
return "<br><br>Gerne kannst du die Hilfe meines Freundes Google in Anspruch nehmen: <a target='_blank' href='https://www.google.com/search?q=" + myQuery + "'>" + myQuery + "</a>"
from chatterbot import ChatBot
from chatterbot.trainers import ChatterBotCorpusTrainer
bot = ChatBot("Chatterbot",
storage_adapter="chatterbot.storage.SQLStorageAdapter")
trainer = ChatterBotCorpusTrainer(bot)
trainer.train("data/learning_corpus") #train the bot
bot.read_only = True #if True, bot will NOT learning after training
