mathtext-fastapi / mathtext_fastapi /conversation_manager.py
Greg Thompson
Improve code modularity and style and incorporate nlu into wormhole prototype
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import os
import json
import requests
from dotenv import load_dotenv
from mathtext_fastapi.nlu import evaluate_message_with_nlu
load_dotenv()
# os.environ.get('SUPABASE_URL')
def create_text_message(message_text, whatsapp_id):
""" Fills a template with the necessary information to send a text message to Whatsapp
Inputs
- message_text: str - the content that the message should display
- whatsapp_id: str - the message recipient's phone number
Outputs
- message_data: dict - a preformatted template with the inputs' values included
"""
message_data = {
"preview_url": False,
"recipient_type": "individual",
"to": whatsapp_id,
"type": "text",
"text": {
"body": message_text
}
}
return message_data
def create_button_objects(button_options):
""" Creates a list of button objects using the input values
Input
- button_options: list - a list of text to be displayed in buttons
Output
- button_arr: list - a list of button objects that use a template filled with the input values
NOTE: Not fully implemented and tested
"""
button_arr = []
for option in button_options:
button_choice = {
"type": "reply",
"reply": {
"id": "inquiry-yes",
"title": option['text']
}
}
button_arr.append(button_choice)
return button_arr
def create_interactive_message(message_text, button_options, whatsapp_id):
""" Fills a template with the necessary information to send a message with button options to Whatsapp
* NOTE: Not fully implemented and tested
* NOTE/TODO: It is possible to create other kinds of messages with the 'interactive message' template
* Documentation: https://whatsapp.turn.io/docs/api/messages#interactive-messages
Inputs
- message_text: str - the content that the message should display
- button_options: list - what each button option should display
- whatsapp_id: str - the message recipient's phone number
"""
button_arr = create_button_objects(button_options)
data = {
"to": whatsapp_id,
"type": "interactive",
"interactive": {
"type": "button",
# "header": { },
"body": {
"text": message_text
},
# "footer": { },
"action": {
"buttons": button_arr
}
}
}
return data
def return_next_conversational_state(context_data, user_message):
""" Evaluates the current state of the conversation to determine resources for the next state of the conversation
Input
- context_data: dict - data about the conversation's current state received from the Turn.io stack
- user_message: str - the message the user sent in response to the state
Output
- message_package: dict - a series of messages and user input to send the user
"""
if context_data['user_message'] == '' and context_data['state'] == 'start-conversation':
message_package = {
'messages': [],
'input_prompt': "Welcome to our math practice. What would you like to try? Type add or subtract.",
'state': "welcome-sequence"
}
elif user_message == 'add':
message_package = {
'messages': [
"Great, let's do some addition",
"First, we'll start with single digits.",
"Type your response as a number. For example, for '1 + 1', you'd write 2."
],
'input_prompt': "Here's the first one... What's 2+2?",
'state': "add-question-sequence"
}
elif user_message == 'subtract':
message_package = {
'messages': [
"Time for some subtraction!",
"Type your response as a number. For example, for '1 - 1', you'd write 0."
],
'input_prompt': "Here's the first one... What's 3-1?",
'state': "subtract-question-sequence"
}
elif user_message == 'exit':
message_package = {
'messages': [
"Great, thanks for practicing math today. Come back any time."
],
'input_prompt': "",
'state': "exit"
}
else:
message_package = {
'messages': [
"Hmmm...sorry friend. I'm not really sure what to do."
],
'input_prompt': "Please type add or subtract to start a math activity.",
'state': "reprompt-menu-options"
}
return message_package
def manage_conversational_response(data_json):
""" Parses message data, determines how to respond to user message at a given conversational state, builds/sends messages, and updates/sends context
Input
- data_json: dict - the data for a message the user sent to Turn.io/Whatsapp
Output
- context: dict - a record of the state at a given point a conversation
TODOs
- implement logging of message
- test interactive messages
- review context object and re-work to use a standardized format
- review ways for more robust error handling
- need to make util functions that apply to both /nlu and /conversation_manager
"""
message_data = data_json.get('message_data', '')
context_data = data_json.get('context_data', '')
whatsapp_id = message_data['author_id']
user_message = message_data['message_body']
# TODO: Need to incorporate nlu_response into wormhole by checking answers against database (spreadsheet?)
nlu_response = evaluate_message_with_nlu(message_data)
message_package = return_next_conversational_state(context_data, user_message)
headers = {
'Authorization': f"Bearer {os.environ.get('TURN_AUTHENTICATION_TOKEN')}",
'Content-Type': 'application/json'
}
# Send all messages for the current state before a user input prompt (text/button input request)
for message in message_package['messages']:
data = create_text_message(message, whatsapp_id)
r = requests.post(f'https://whatsapp.turn.io/v1/messages', data=json.dumps(data), headers=headers)
# Update the context object with the new state of the conversation
context = {
"context":{
"user": whatsapp_id,
"state": message_package['state'],
"bot_message": message_package['input_prompt'],
"user_message": user_message,
"type": 'ask'
}
}
return context
# data = {
# "to": whatsapp_id,
# "type": "interactive",
# "interactive": {
# "type": "button",
# # "header": { },
# "body": {
# "text": "Did I answer your question?"
# },
# # "footer": { },
# "action": {
# "buttons": [
# {
# "type": "reply",
# "reply": {
# "id": "inquiry-yes",
# "title": "Yes"
# }
# },
# {
# "type": "reply",
# "reply": {
# "id": "inquiry-no",
# "title": "No"
# }
# }
# ]
# }
# }
# }