rasa/jupyter.py
def chat(model_path: Text = None, agent: 'Agent' = None,
         interpreter: NaturalLanguageInterpreter = None) -> None:
    """Chat to the bot within a Jupyter notebook.

    Args:
        model_path: Path to a Rasa Stack model.
        agent: Rasa Core agent (used if no Rasa Stack model given).
        interpreter: Rasa NLU interpreter (used with Rasa Core agent if no
                     Rasa Stack model is given).
    """

    if model_path:
        from rasa.run import create_agent
        unpacked = model.get_model(model_path)
        agent = create_agent(unpacked)
    elif agent and interpreter:
        # HACK: this skips loading the interpreter and directly
        # sets it afterwards
        nlu_interpreter = RasaNLUInterpreter("skip this and use given "
                                             "interpreter", lazy_init=True)
        nlu_interpreter.interpreter = interpreter
        agent.interpreter = interpreter
    else:
        print_error("You either have to define a model path or an agent and "
                    "an interpreter.")

    print("Your bot is ready to talk! Type your messages here or send '/stop'.")
    loop = asyncio.get_event_loop()
    while True:
        message = input()
        if message == '/stop':
            break

        responses = loop.run_until_complete(agent.handle_text(message))
        for response in responses:
            _display_bot_response(response)
Chat to the bot within a Jupyter notebook.

    Args:
        model_path: Path to a Rasa Stack model.
        agent: Rasa Core agent (used if no Rasa Stack model given).
        interpreter: Rasa NLU interpreter (used with Rasa Core agent if no
                     Rasa Stack model is given).
    
Chat to the bot within a Jupyter notebook.
Chat to the bot within a Jupyter notebook .
def chat(model_path: Text = None, agent: 'Agent' = None,
         interpreter: NaturalLanguageInterpreter = None) -> None:
    if model_path:
        from rasa.run import create_agent
        unpacked = model.get_model(model_path)
        agent = create_agent(unpacked)
    elif agent and interpreter:
        nlu_interpreter = RasaNLUInterpreter("skip this and use given "
                                             "interpreter", lazy_init=True)
        nlu_interpreter.interpreter = interpreter
        agent.interpreter = interpreter
    else:
        print_error("You either have to define a model path or an agent and "
                    "an interpreter.")
    print("Your bot is ready to talk! Type your messages here or send '/stop'.")
    loop = asyncio.get_event_loop()
    while True:
        message = input()
        if message == '/stop':
            break
        responses = loop.run_until_complete(agent.handle_text(message))
        for response in responses:
            _display_bot_response(response)
def chat ( model_path : Text = None , agent : 'Agent' = None , interpreter : NaturalLanguageInterpreter = None ) -> None : if model_path : from rasa . run import create_agent unpacked = model . get_model ( model_path ) agent = create_agent ( unpacked ) elif agent and interpreter : nlu_interpreter = RasaNLUInterpreter ( "skip this and use given " "interpreter" , lazy_init = True ) nlu_interpreter . interpreter = interpreter agent . interpreter = interpreter else : print_error ( "You either have to define a model path or an agent and " "an interpreter." ) print ( "Your bot is ready to talk! Type your messages here or send '/stop'." ) loop = asyncio . get_event_loop ( ) while True : message = input ( ) if message == '/stop' : break responses = loop . run_until_complete ( agent . handle_text ( message ) ) for response in responses : _display_bot_response ( response )
Chat to the bot within a Jupyter notebook.
Chat to the bot within a Jupyter notebook .
"""Chat to the bot within a Jupyter notebook.

    Args:
        model_path: Path to a Rasa Stack model.
        agent: Rasa Core agent (used if no Rasa Stack model given).
        interpreter: Rasa NLU interpreter (used with Rasa Core agent if no
                     Rasa Stack model is given).
    """ # HACK: this skips loading the interpreter and directly # sets it afterwards
model_path
Text
Path to a Rasa Stack model.
Path to a Rasa Stack model .
agent
'Agent'
Rasa Core agent (used if no Rasa Stack model given).
Rasa Core agent ( used if no Rasa Stack model given ) .
interpreter
NaturalLanguageInterpreter
Rasa NLU interpreter (used with Rasa Core agent if no
Rasa Stack model is given).
Rasa NLU interpreter ( used with Rasa Core agent if no Rasa Stack model is given ) .