File size: 1,543 Bytes
bd7cdc8 4667e53 bd7cdc8 4667e53 bd7cdc8 b7958ec bd7cdc8 6b2e4b9 bd7cdc8 9891d22 bd7cdc8 cf35bce bd7cdc8 cf35bce bd7cdc8 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 |
from flow_modules.aiflows.HumanStandardInputFlowModule import HumanStandardInputFlow
from typing import Dict, Any
from aiflows.messages import UpdateMessage_Generic
from aiflows.utils import logging
log = logging.get_logger(f"aiflows.{__name__}")
# TODO: extract this flow to a seperate flow module for modularity.
class ExtLibAskUserFlow(HumanStandardInputFlow):
"""This class is used to ask for user feedback whenever the controller is unsure of something, or need confirmation, etc.
*Expected Input*:
- `question`: The question asked by the controller
*Expected Behaviour*:
- The question is displayed, and the user gives feedback by inputing string.
*Expected Ouput*:
- `result`: The input of the user.
- `summary`: The summary that will be written by the caller.
"""
def run(self,
input_data: Dict[str, Any]) -> Dict[str, Any]:
query_message = self._get_message(self.query_message_prompt_template, input_data)
state_update_message = UpdateMessage_Generic(
created_by=self.flow_config['name'],
updated_flow=self.flow_config["name"],
data={"query_message": query_message},
)
self._log_message(state_update_message)
log.info(query_message)
human_input = self._read_input()
question = input_data["question"]
response = {}
response["result"] = human_input
response["summary"] = f"Question raised: {question}; answer of user: {human_input}"
return response |