def run_online(interpreter,domain_file="./domain.yml",training_data_file='./backend/stories.md'):
agent = Agent(domain_file,
policies=[MemoizationPolicy(max_history=2), KerasPolicy()],
interpreter=interpreter)
data = agent.load_data(training_data_file)
agent.train(data,
batch_size=50,
epochs=200,
max_training_samples=300)
online.serve_agent(agent)
return agent
def run_weather_online(interpreter,
domain_file="weather_domain.yml",
training_data_file='data/stories.md'):
action_endpoint = EndpointConfig(url="http://localhost:5055/webhook")
agent = Agent(domain_file,
policies=[MemoizationPolicy(max_history=2),
KerasPolicy()],
interpreter=interpreter,
action_endpoint=action_endpoint)
data = agent.load_data(training_data_file)
agent.train(data, batch_size=50, epochs=200, max_training_samples=300)
online.serve_agent(agent)
return agent
def run_online(domain_file="domain.yml", training_data_file="data/stories.md"):
interpreter = RasaNLUInterpreter('models/nlu/default/latest_nlu')
action_endpoint = EndpointConfig(url="http://localhost:5055/webhook")
agent = Agent(
domain_file,
policies=[MemoizationPolicy(max_history=2),
KerasPolicy(), fallback],
interpreter=interpreter,
action_endpoint=action_endpoint)
data = agent.load_data(training_data_file)
agent.train(data, batch_size=50, epochs=200, max_training_samples=300)
online.serve_agent(agent)
return agent