Spaces:
Runtime error
Runtime error
nlu assertions to log error messages for all possible errors in payload data format
Browse files
mathtext_fastapi/conversation_manager.py
CHANGED
@@ -39,6 +39,7 @@ def create_text_message(message_text, whatsapp_id):
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"preview_url": False,
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"recipient_type": "individual",
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"to": whatsapp_id,
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"type": "text",
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"text": {
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"body": message_text
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@@ -136,6 +137,9 @@ def manage_math_quiz_fsm(user_message, contact_uuid, type):
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# Make a completely new entry
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if fsm_check.data == []:
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if type == 'addition':
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math_quiz_state_machine = MathQuizFSM()
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else:
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"preview_url": False,
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"recipient_type": "individual",
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"to": whatsapp_id,
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# FIXME: Better to use "message_type" (but be careful with refactor)
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"type": "text",
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"text": {
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"body": message_text
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# Make a completely new entry
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if fsm_check.data == []:
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# FIXME: Try not to use the Python reserved keyword `type` as a variable name
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# It's better to use `kind` or `convo_type` or `convo_name`
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# And the variable `type` is not defined here so I don't understand how this is working at all.
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if type == 'addition':
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math_quiz_state_machine = MathQuizFSM()
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else:
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mathtext_fastapi/nlu.py
CHANGED
@@ -1,23 +1,20 @@
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from collections.abc import Mapping
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from logging import getLogger
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import datetime as dt
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import re
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from fuzzywuzzy import fuzz
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from mathtext_fastapi.logging import prepare_message_data_for_logging
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from mathtext.sentiment import sentiment
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from mathtext.text2int import text2int
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from mathtext_fastapi.intent_classification import
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log = getLogger(__name__)
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ERROR_CODE = 32202
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-
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def build_nlu_response_object(type, data, confidence):
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""" Turns nlu results into an object to send back to Turn.io
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Inputs
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-
-
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- data: str/int - the student message
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- confidence: - the nlu confidence score (sentiment) or '' (integer)
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@@ -27,7 +24,11 @@ def build_nlu_response_object(type, data, confidence):
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>>> build_nlu_response_object('sentiment', 'POSITIVE', 0.99)
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{'type': 'sentiment', 'data': 'POSITIVE', 'confidence': 0.99}
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"""
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return {
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# def test_for_float_or_int(message_data, message_text):
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@@ -167,6 +168,86 @@ def payload_is_valid(payload_object):
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)
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)
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def evaluate_message_with_nlu(message_data):
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""" Process a student's message using NLU functions and send the result
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@@ -182,14 +263,15 @@ def evaluate_message_with_nlu(message_data):
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log.info(f'Starting evaluate message: {message_data}')
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if not payload_is_valid(message_data):
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-
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try:
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message_text = str(message_data.get('message_body', ''))
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except:
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log.error(f'Invalid request payload: {message_data}')
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# use python logging system to do this//
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return {'type': 'error', 'data':
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# Run intent classification only for keywords
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intent_api_response = run_intent_classification(message_text)
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@@ -199,7 +281,7 @@ def evaluate_message_with_nlu(message_data):
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number_api_resp = text2int(message_text.lower())
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if number_api_resp ==
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# Run intent classification with logistic regression model
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predicted_label = predict_message_intent(message_text)
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if predicted_label['confidence'] > 0.01:
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from collections.abc import Mapping
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from logging import getLogger
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import datetime as dt
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from fuzzywuzzy import fuzz
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from mathtext_fastapi.logging import prepare_message_data_for_logging
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from mathtext.sentiment import sentiment
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from mathtext.text2int import text2int, TOKENS2INT_ERROR_INT
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from mathtext_fastapi.intent_classification import predict_message_intent
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log = getLogger(__name__)
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def build_nlu_response_object(nlu_type, data, confidence):
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""" Turns nlu results into an object to send back to Turn.io
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Inputs
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- nlu_type: str - the type of nlu run (integer or sentiment-analysis)
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- data: str/int - the student message
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- confidence: - the nlu confidence score (sentiment) or '' (integer)
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>>> build_nlu_response_object('sentiment', 'POSITIVE', 0.99)
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{'type': 'sentiment', 'data': 'POSITIVE', 'confidence': 0.99}
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"""
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return {
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'type': nlu_type,
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'data': data,
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'confidence': confidence
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}
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# def test_for_float_or_int(message_data, message_text):
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)
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def log_payload_errors(payload_object):
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errors = []
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try:
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assert isinstance(payload_object, Mapping)
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except Exception as e:
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log.error(f'Invalid HTTP request payload object: {e}')
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errors.append(e)
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try:
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assert isinstance(payload_object.get('author_id'), str)
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except Exception as e:
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log.error(f'Invalid HTTP request payload object: {e}')
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errors.append(e)
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try:
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assert isinstance(payload_object.get('author_type'), str)
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except Exception as e:
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log.error(f'Invalid HTTP request payload object: {e}')
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errors.append(e)
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try:
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assert isinstance(payload_object.get('contact_uuid'), str)
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except Exception as e:
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log.error(f'Invalid HTTP request payload object: {e}')
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errors.append(e)
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try:
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assert isinstance(payload_object.get('message_body'), str)
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except Exception as e:
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log.error(f'Invalid HTTP request payload object: {e}')
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errors.append(e)
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try:
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assert isinstance(payload_object.get('message_direction'), str)
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except Exception as e:
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log.error(f'Invalid HTTP request payload object: {e}')
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errors.append(e)
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try:
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assert isinstance(payload_object.get('inbound'), str)
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except Exception as e:
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log.error(f'Invalid HTTP request payload object: {e}')
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errors.append(e)
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try:
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assert isinstance(payload_object.get('message_id'), str)
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except Exception as e:
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log.error(f'Invalid HTTP request payload object: {e}')
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errors.append(e)
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try:
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assert isinstance(payload_object.get('message_inserted_at'), str)
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except Exception as e:
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log.error(f'Invalid HTTP request payload object: {e}')
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errors.append(e)
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try:
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assert isinstance(payload_object.get('message_updated_at'), str)
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except Exception as e:
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log.error(f'Invalid HTTP request payload object: {e}')
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errors.append(e)
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try:
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assert isinstance(payload_object.get('message_inserted_at'), str)
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except Exception as e:
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log.error(f'Invalid HTTP request payload object: {e}')
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errors.append(e)
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try:
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assert isinstance(payload_object.get('message_updated_at'), str)
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except Exception as e:
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log.error(f'Invalid HTTP request payload object: {e}')
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errors.append(e)
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try:
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assert isinstance(
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dt.datetime.fromisoformat(payload_object.get('message_inserted_at')),
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dt.datetime
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)
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except Exception as e:
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log.error(f'Invalid HTTP request payload object: {e}')
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errors.append(e)
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try:
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isinstance(
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dt.datetime.fromisoformat(payload_object.get('message_updated_at')),
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dt.datetime
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)
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except Exception as e:
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log.error(f'Invalid HTTP request payload object: {e}')
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errors.append(e)
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return errors
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def evaluate_message_with_nlu(message_data):
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""" Process a student's message using NLU functions and send the result
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log.info(f'Starting evaluate message: {message_data}')
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if not payload_is_valid(message_data):
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log_payload_errors(message_data)
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return {'type': 'error', 'data': TOKENS2INT_ERROR_INT, 'confidence': 0}
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try:
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message_text = str(message_data.get('message_body', ''))
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except:
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log.error(f'Invalid request payload: {message_data}')
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# use python logging system to do this//
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return {'type': 'error', 'data': TOKENS2INT_ERROR_INT, 'confidence': 0}
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# Run intent classification only for keywords
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intent_api_response = run_intent_classification(message_text)
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number_api_resp = text2int(message_text.lower())
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if number_api_resp == TOKENS2INT_ERROR_INT:
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# Run intent classification with logistic regression model
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predicted_label = predict_message_intent(message_text)
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if predicted_label['confidence'] > 0.01:
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