async def _predict_till_next_listen(
endpoint: EndpointConfig,
sender_id: Text,
finetune: bool,
sender_ids: List[Text],
plot_file: Optional[Text],
) -> None:
"""Predict and validate actions until we need to wait for a user msg."""
listen = False
while not listen:
result = await request_prediction(endpoint, sender_id)
predictions = result.get("scores")
probabilities = [prediction["score"] for prediction in predictions]
pred_out = int(np.argmax(probabilities))
action_name = predictions[pred_out].get("action")
policy = result.get("policy")
confidence = result.get("confidence")
await _print_history(sender_id, endpoint)
await _plot_trackers(
sender_ids, plot_file, endpoint, unconfirmed=[ActionExecuted(action_name)]
)
listen = await _validate_action(
action_name,
policy,
confidence,
predictions,
endpoint,
sender_id,
finetune=finetune,
)
await _plot_trackers(sender_ids, plot_file, endpoint)
tracker_dump = await retrieve_tracker(
endpoint, sender_id, EventVerbosity.AFTER_RESTART
)
events = tracker_dump.get("events", [])
if len(events) >= 2:
last_event = events[-2] # last event before action_listen
# if bot message includes buttons the user will get a list choice to reply
# the list choice is displayed in place of action listen
if last_event.get("event") == BotUttered.type_name and last_event["data"].get(
"buttons", None
):
data = last_event["data"]
message = last_event.get("text", "")
choices = [
button_to_string(button, idx)
for idx, button in enumerate(data.get("buttons"))
]
question = questionary.select(message, choices)
button_payload = cliutils.payload_from_button_question(question)
await send_message(endpoint, sender_id, button_payload)
def get_user_input(button_question: questionary.Question) -> Optional[Text]:
if button_question is not None:
response = cli_utils.payload_from_button_question(button_question)
if response == cli_utils.FREE_TEXT_INPUT_PROMPT:
# Re-prompt user with a free text input
response = get_user_input(None)
else:
response = questionary.text(
"",
qmark="Your input ->",
style=Style([("qmark", "#b373d6"), ("", "#b373d6")]),
).ask()
return response.strip() if response is not None else None
def _get_user_input(previous_response: Optional[Dict[str, Any]]) -> Optional[Text]:
button_response = None
if previous_response is not None:
button_response = _print_bot_output(previous_response, is_latest_message=True)
if button_response is not None:
response = cli_utils.payload_from_button_question(button_response)
if response == cli_utils.FREE_TEXT_INPUT_PROMPT:
# Re-prompt user with a free text input
response = _get_user_input({})
else:
response = questionary.text(
"",
qmark="Your input ->",
style=Style([("qmark", "#b373d6"), ("", "#b373d6")]),
).ask()
return response.strip() if response is not None else None
def _user_input(button_question: questionary.Question) -> Optional[Text]:
exit_text = INTENT_MESSAGE_PREFIX + "stop"
if button_question is not None:
response = cli_utils.payload_from_button_question(button_question)
if response == cli_utils.FREE_TEXT_INPUT_PROMPT:
# Re-prompt user with a free text input
response = _user_input(None)
else:
response = questionary.text(
"",
qmark="Your input ->",
style=Style([("qmark", "#b373d6"), ("", "#b373d6")]),
).ask()
text = response.strip() if response is not None else None
if not sett.is_disable_analyse:
if text is not None and not text.startswith(INTENT_MESSAGE_PREFIX):
subprocess.call(['sagas', 'vis', text, sett.lang])
return text