Fix merge conflicts

README.md

@@ -6,7 +6,6 @@ colorTo: red
 sdk: docker
 pinned: false
 license: agpl-3.0
-duplicated_from: thompsgj/mathtext-fastapi
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

@@ -17,6 +17,7 @@ from pydantic import BaseModel
 
 from mathtext_fastapi.logging import prepare_message_data_for_logging
 from mathtext_fastapi.conversation_manager import manage_conversation_response
+from mathtext_fastapi.v2_conversation_manager import manage_conversation_response
 from mathtext_fastapi.nlu import evaluate_message_with_nlu
 from mathtext_fastapi.nlu import run_intent_classification
 
@@ -56,7 +57,44 @@ def text2int_ep(content: Text = None):
     return JSONResponse(content=content)
 
 
+<<<<<<< HEAD
 @app.post("/manager")
+=======
+@app.post("/v1/manager")
+async def programmatic_message_manager(request: Request):
+    """
+    Calls conversation management function to determine the next state
+
+    Input
+    request.body: dict - message data for the most recent user response
+    {
+        "author_id": "+47897891",
+        "contact_uuid": "j43hk26-2hjl-43jk-hnk2-k4ljl46j0ds09",
+        "author_type": "OWNER",
+        "message_body": "a test message",
+        "message_direction": "inbound",
+        "message_id": "ABJAK64jlk3-agjkl2QHFAFH",
+        "message_inserted_at": "2022-07-05T04:00:34.03352Z",
+        "message_updated_at": "2023-02-14T03:54:19.342950Z",
+    }
+
+    Output
+    context: dict - the information for the current state
+    {
+        "user": "47897891",
+        "state": "welcome-message-state",
+        "bot_message": "Welcome to Rori!",
+        "user_message": "",
+        "type": "ask"
+    }
+    """
+    data_dict = await request.json()
+    context = manage_conversation_response(data_dict)
+    return JSONResponse(context)
+
+
+@app.post("/v2/manager")
+>>>>>>> feature-wormhole
 async def programmatic_message_manager(request: Request):
     """
     Calls conversation management function to determine the next state

mathtext_fastapi/curriculum_mapper.py

@@ -0,0 +1,183 @@
+import numpy as np
+import pandas as pd
+import re
+
+from pathlib import Path
+
+
+def read_and_preprocess_spreadsheet(file_name):
+    """ Creates a pandas dataframe from the curriculum overview spreadsheet """
+    DATA_DIR = Path(__file__).parent.parent / "mathtext_fastapi" / "data" / file_name
+    script_df = pd.read_excel(DATA_DIR, engine='openpyxl')
+    # Ensures the grade level columns are integers instead of floats
+    script_df.columns = script_df.columns[:2].tolist() + script_df.columns[2:11].astype(int).astype(str).tolist() + script_df.columns[11:].tolist()
+    script_df.fillna('', inplace=True)
+    return script_df
+
+
+def extract_skill_code(skill):
+    """ Looks within a curricular skill description for its descriptive code
+
+    Input
+    - skill: str - a brief description of a curricular skill
+
+    >>> extract_skill_code('A3.3.4 - Solve inequalities')
+    'A3.3.4'
+    >>> extract_skill_code('A3.3.2 - Graph linear equations, and identify the x- and y-intercepts or the slope of a line')
+    'A3.3.2'
+    """
+    pattern = r'[A-Z][0-9]\.\d+\.\d+'
+    result = re.search(pattern, skill)
+    return result.group()
+
+
+def build_horizontal_transitions(script_df):
+    """ Build a list of transitional relationships within a curricular skill
+
+    Inputs
+    - script_df: pandas dataframe - an overview of the curriculum skills by grade level
+
+    Output
+    - horizontal_transitions: array of arrays - transition data with label, from state, and to state
+
+    >>> script_df = read_and_preprocess_spreadsheet('curriculum_framework_for_tests.xlsx')
+    >>> build_horizontal_transitions(script_df)
+    [['right', 'N1.1.1_G1', 'N1.1.1_G2'], ['right', 'N1.1.1_G2', 'N1.1.1_G3'], ['right', 'N1.1.1_G3', 'N1.1.1_G4'], ['right', 'N1.1.1_G4', 'N1.1.1_G5'], ['right', 'N1.1.1_G5', 'N1.1.1_G6'], ['left', 'N1.1.1_G6', 'N1.1.1_G5'], ['left', 'N1.1.1_G5', 'N1.1.1_G4'], ['left', 'N1.1.1_G4', 'N1.1.1_G3'], ['left', 'N1.1.1_G3', 'N1.1.1_G2'], ['left', 'N1.1.1_G2', 'N1.1.1_G1'], ['right', 'N1.1.2_G1', 'N1.1.2_G2'], ['right', 'N1.1.2_G2', 'N1.1.2_G3'], ['right', 'N1.1.2_G3', 'N1.1.2_G4'], ['right', 'N1.1.2_G4', 'N1.1.2_G5'], ['right', 'N1.1.2_G5', 'N1.1.2_G6'], ['left', 'N1.1.2_G6', 'N1.1.2_G5'], ['left', 'N1.1.2_G5', 'N1.1.2_G4'], ['left', 'N1.1.2_G4', 'N1.1.2_G3'], ['left', 'N1.1.2_G3', 'N1.1.2_G2'], ['left', 'N1.1.2_G2', 'N1.1.2_G1']]
+    """
+    horizontal_transitions = []
+    for index, row in script_df.iterrows():     
+        skill_code = extract_skill_code(row['Knowledge or Skill'])
+
+        rightward_matches = []
+        for i in range(9):
+            # Grade column
+            current_grade = i+1
+            if row[current_grade].lower().strip() == 'x':
+                rightward_matches.append(i)
+            
+        for match in rightward_matches:
+            if rightward_matches[-1] != match:
+                horizontal_transitions.append([
+                    "right",
+                    f"{skill_code}_G{match}",
+                    f"{skill_code}_G{match+1}"
+                ])
+
+        leftward_matches = []
+        for i in reversed(range(9)):
+            current_grade = i
+            if row[current_grade].lower().strip() == 'x':
+                leftward_matches.append(i)
+
+        for match in leftward_matches:
+            if leftward_matches[0] != match:
+                horizontal_transitions.append([
+                    "left",
+                    f"{skill_code}_G{match}",
+                    f"{skill_code}_G{match-1}"
+                ])
+
+    return horizontal_transitions
+
+
+def gather_all_vertical_matches(script_df):
+    """ Build a list of transitional relationships within a grade level across skills
+
+    Inputs
+    - script_df: pandas dataframe - an overview of the curriculum skills by grade level
+
+    Output
+    - all_matches: array of arrays - represents skills at each grade level
+
+    >>> script_df = read_and_preprocess_spreadsheet('curriculum_framework_for_tests.xlsx')
+    >>> gather_all_vertical_matches(script_df)
+    [['N1.1.1', '1'], ['N1.1.2', '1'], ['N1.1.1', '2'], ['N1.1.2', '2'], ['N1.1.1', '3'], ['N1.1.2', '3'], ['N1.1.1', '4'], ['N1.1.2', '4'], ['N1.1.1', '5'], ['N1.1.2', '5'], ['N1.1.1', '6'], ['N1.1.2', '6']]
+    """
+    all_matches = []
+    columns = ['1', '2', '3', '4', '5', '6', '7', '8', '9']
+
+    for column in columns:
+        for index, value in script_df[column].iteritems():
+            row_num = index + 1
+            if value == 'x':
+                # Extract skill code
+                skill_code = extract_skill_code(
+                    script_df['Knowledge or Skill'][row_num-1]
+                )
+
+                all_matches.append([skill_code, column])
+    return all_matches
+
+
+def build_vertical_transitions(script_df):
+    """ Build a list of transitional relationships within a grade level across skills
+
+    Inputs
+    - script_df: pandas dataframe - an overview of the curriculum skills by grade level
+
+    Output
+    - vertical_transitions: array of arrays - transition data with label, from state, and to state
+
+    >>> script_df = read_and_preprocess_spreadsheet('curriculum_framework_for_tests.xlsx')
+    >>> build_vertical_transitions(script_df)
+    [['down', 'N1.1.1_G1', 'N1.1.2_G1'], ['down', 'N1.1.2_G1', 'N1.1.1_G1'], ['down', 'N1.1.1_G2', 'N1.1.2_G2'], ['down', 'N1.1.2_G2', 'N1.1.1_G2'], ['down', 'N1.1.1_G3', 'N1.1.2_G3'], ['down', 'N1.1.2_G3', 'N1.1.1_G3'], ['down', 'N1.1.1_G4', 'N1.1.2_G4'], ['down', 'N1.1.2_G4', 'N1.1.1_G4'], ['down', 'N1.1.1_G5', 'N1.1.2_G5'], ['down', 'N1.1.2_G5', 'N1.1.1_G5'], ['down', 'N1.1.1_G6', 'N1.1.2_G6'], ['up', 'N1.1.2_G6', 'N1.1.1_G6'], ['up', 'N1.1.1_G6', 'N1.1.2_G6'], ['up', 'N1.1.2_G5', 'N1.1.1_G5'], ['up', 'N1.1.1_G5', 'N1.1.2_G5'], ['up', 'N1.1.2_G4', 'N1.1.1_G4'], ['up', 'N1.1.1_G4', 'N1.1.2_G4'], ['up', 'N1.1.2_G3', 'N1.1.1_G3'], ['up', 'N1.1.1_G3', 'N1.1.2_G3'], ['up', 'N1.1.2_G2', 'N1.1.1_G2'], ['up', 'N1.1.1_G2', 'N1.1.2_G2'], ['up', 'N1.1.2_G1', 'N1.1.1_G1']]
+    """
+    vertical_transitions = []
+
+    all_matches = gather_all_vertical_matches(script_df)
+
+    # Downward
+    for index, match in enumerate(all_matches):
+        skill = match[0]
+        row_num = match[1]
+        if all_matches[-1] != match:
+            vertical_transitions.append([
+                "down",
+                f"{skill}_G{row_num}",
+                f"{all_matches[index+1][0]}_G{row_num}"
+            ])
+
+    # Upward
+    for index, match in reversed(list(enumerate(all_matches))):
+        skill = match[0]
+        row_num = match[1]
+        if all_matches[0] != match:
+            vertical_transitions.append([
+                "up",
+                f"{skill}_G{row_num}",
+                f"{all_matches[index-1][0]}_G{row_num}"
+            ])
+    
+    return vertical_transitions
+
+
+def build_all_states(all_transitions):
+    """ Creates an array with all state labels for the curriculum
+
+    Input
+    - all_transitions: list of lists - all possible up, down, left, or right transitions in curriculum
+
+    Output
+    - all_states: list - a collection of state labels (skill code and grade number)
+    
+    >>> all_transitions = [['right', 'N1.1.1_G1', 'N1.1.1_G2'], ['right', 'N1.1.1_G2', 'N1.1.1_G3'], ['right', 'N1.1.1_G3', 'N1.1.1_G4'], ['right', 'N1.1.1_G4', 'N1.1.1_G5'], ['right', 'N1.1.1_G5', 'N1.1.1_G6'], ['left', 'N1.1.1_G6', 'N1.1.1_G5'], ['left', 'N1.1.1_G5', 'N1.1.1_G4'], ['left', 'N1.1.1_G4', 'N1.1.1_G3'], ['left', 'N1.1.1_G3', 'N1.1.1_G2'], ['left', 'N1.1.1_G2', 'N1.1.1_G1'], ['right', 'N1.1.2_G1', 'N1.1.2_G2'], ['right', 'N1.1.2_G2', 'N1.1.2_G3'], ['right', 'N1.1.2_G3', 'N1.1.2_G4'], ['right', 'N1.1.2_G4', 'N1.1.2_G5'], ['right', 'N1.1.2_G5', 'N1.1.2_G6'], ['left', 'N1.1.2_G6', 'N1.1.2_G5'], ['left', 'N1.1.2_G5', 'N1.1.2_G4'], ['left', 'N1.1.2_G4', 'N1.1.2_G3'], ['left', 'N1.1.2_G3', 'N1.1.2_G2'], ['left', 'N1.1.2_G2', 'N1.1.2_G1'], ['down', 'N1.1.1_G1', 'N1.1.2_G1'], ['down', 'N1.1.2_G1', 'N1.1.1_G1'], ['down', 'N1.1.1_G2', 'N1.1.2_G2'], ['down', 'N1.1.2_G2', 'N1.1.1_G2'], ['down', 'N1.1.1_G3', 'N1.1.2_G3'], ['down', 'N1.1.2_G3', 'N1.1.1_G3'], ['down', 'N1.1.1_G4', 'N1.1.2_G4'], ['down', 'N1.1.2_G4', 'N1.1.1_G4'], ['down', 'N1.1.1_G5', 'N1.1.2_G5'], ['down', 'N1.1.2_G5', 'N1.1.1_G5'], ['down', 'N1.1.1_G6', 'N1.1.2_G6'], ['up', 'N1.1.2_G6', 'N1.1.1_G6'], ['up', 'N1.1.1_G6', 'N1.1.2_G6'], ['up', 'N1.1.2_G5', 'N1.1.1_G5'], ['up', 'N1.1.1_G5', 'N1.1.2_G5'], ['up', 'N1.1.2_G4', 'N1.1.1_G4'], ['up', 'N1.1.1_G4', 'N1.1.2_G4'], ['up', 'N1.1.2_G3', 'N1.1.1_G3'], ['up', 'N1.1.1_G3', 'N1.1.2_G3'], ['up', 'N1.1.2_G2', 'N1.1.1_G2'], ['up', 'N1.1.1_G2', 'N1.1.2_G2'], ['up', 'N1.1.2_G1', 'N1.1.1_G1']]
+    >>> build_all_states(all_transitions)
+    ['N1.1.1_G1', 'N1.1.1_G2', 'N1.1.1_G3', 'N1.1.1_G4', 'N1.1.1_G5', 'N1.1.1_G6', 'N1.1.2_G1', 'N1.1.2_G2', 'N1.1.2_G3', 'N1.1.2_G4', 'N1.1.2_G5', 'N1.1.2_G6']
+    """
+    all_states = []
+    for transition in all_transitions:
+        for index, state in enumerate(transition):
+            if index == 0:
+                continue   
+            if state not in all_states:
+                all_states.append(state)
+    return all_states
+
+
+def build_curriculum_logic():
+    script_df = read_and_preprocess_spreadsheet('Rori_Framework_v1.xlsx')
+    horizontal_transitions = build_horizontal_transitions(script_df)
+    vertical_transitions = build_vertical_transitions(script_df)
+    all_transitions = horizontal_transitions + vertical_transitions
+    all_states = build_all_states(all_transitions)
+    return all_states, all_transitions

mathtext_fastapi/data/text2int_results.csv

@@ -20,10 +20,17 @@ eight oh,80.0,8.0,False
 eighty,80.0,80.0,True
 ate,8.0,1.0,False
 double eight,88.0,8.0,False
+<<<<<<< HEAD
 eight three seven five three O nine,8375309.0,8375329.0,False
 eight three seven five three oh nine,8375309.0,8375309.0,True
 eight three seven five three zero nine,8375309.0,8375309.0,True
 eight three seven five three oh ni-ee-ine,8375309.0,837530619.0,False
+=======
+eight three seven five three O nine,8375309.0,8375319.0,False
+eight three seven five three oh nine,8375309.0,8375309.0,True
+eight three seven five three zero nine,8375309.0,8375309.0,True
+eight three seven five three oh ni-ee-ine,8375309.0,837530111.0,False
+>>>>>>> feature-wormhole
 two eight,28.0,16.0,False
 seven oh eleven,7011.0,77.0,False
 seven elevens,77.0,77.0,True
@@ -31,10 +38,17 @@ seven eleven,711.0,77.0,False
 ninety nine oh five,9905.0,149.0,False
 seven 0 seven 0 seven 0 seven,7070707.0,7070707.0,True
 123 hundred,123000.0,223.0,False
+<<<<<<< HEAD
 5 o 5,505.0,525.0,False
 15 o 5,1505.0,22.0,False
 15-o 5,1505.0,22.0,False
 15 o-5,1505.0,22.0,False
+=======
+5 o 5,505.0,515.0,False
+15 o 5,1505.0,21.0,False
+15-o 5,1505.0,21.0,False
+15 o-5,1505.0,21.0,False
+>>>>>>> feature-wormhole
 911-thousand,911000.0,911000.0,True
 twenty-two twenty-two,2222.0,44.0,False
 twenty-two twenty-twos,484.0,44.0,False

mathtext_fastapi/global_state_manager.py

@@ -0,0 +1,23 @@
+from transitions import Machine
+from mathtext_fastapi.curriculum_mapper import build_curriculum_logic
+
+all_states, all_transitions = build_curriculum_logic()
+
+class GlobalStateManager(object):
+    states = all_states
+
+    transitions = all_transitions
+
+    def __init__(
+        self,
+        initial_state='N1.1.1_G1',
+    ):
+        self.machine = Machine(
+            model=self,
+            states=GlobalStateManager.states,
+            transitions=GlobalStateManager.transitions,
+            initial=initial_state
+        )
+
+
+curriculum = GlobalStateManager()

mathtext_fastapi/nlu.py

@@ -155,6 +155,7 @@ def evaluate_message_with_nlu(message_data):
         predicted_label = predict_message_intent(message_text)
         if predicted_label['confidence'] > 0.01:
             nlu_response = predicted_label
+<<<<<<< HEAD
             return nlu_response
 
         # Run sentiment analysis
@@ -164,6 +165,16 @@ def evaluate_message_with_nlu(message_data):
             sentiment_api_resp[0]['label'],
             sentiment_api_resp[0]['score']
         )
+=======
+        else:
+            # Run sentiment analysis
+            sentiment_api_resp = sentiment(message_text)
+            nlu_response = build_nlu_response_object(
+                'sentiment',
+                sentiment_api_resp[0]['label'],
+                sentiment_api_resp[0]['score']
+            )
+>>>>>>> feature-wormhole
     else:
         nlu_response = build_nlu_response_object(
             'integer',

mathtext_fastapi/v2_conversation_manager.py

@@ -0,0 +1,196 @@
+import base64
+import copy
+import dill
+import os
+import json
+import jsonpickle
+import pickle
+import random
+import requests
+import mathtext_fastapi.global_state_manager as gsm
+
+from dotenv import load_dotenv
+from mathtext_fastapi.nlu import evaluate_message_with_nlu
+from mathtext_fastapi.math_quiz_fsm import MathQuizFSM
+from mathtext_fastapi.math_subtraction_fsm import MathSubtractionFSM
+from supabase import create_client
+from transitions import Machine
+
+from scripts.quiz.generators import start_interactive_math
+from scripts.quiz.hints import generate_hint
+
+load_dotenv()
+
+SUPA = create_client(
+    os.environ.get('SUPABASE_URL'),
+    os.environ.get('SUPABASE_KEY')
+)
+
+
+def pickle_and_encode_state_machine(state_machine):
+    dump = pickle.dumps(state_machine)
+    dump_encoded = base64.b64encode(dump).decode('utf-8')
+    return dump_encoded
+
+
+def manage_math_quiz_fsm(user_message, contact_uuid, type):
+    fsm_check = SUPA.table('state_machines').select("*").eq(
+        "contact_uuid",
+        contact_uuid
+    ).execute()
+
+    # This doesn't allow for when one FSM is present and the other is empty
+    """
+    1
+    data=[] count=None
+    
+    2
+    data=[{'id': 29, 'contact_uuid': 'j43hk26-2hjl-43jk-hnk2-k4ljl46j0ds09', 'addition3': None, 'subtraction': None, 'addition': 
+
+    - but problem is there is no subtraction , but it's assuming there's a subtration
+
+    Cases
+    - make a completely new record
+    - update an existing record with an existing FSM
+    - update an existing record without an existing FSM
+    """
+    print("MATH QUIZ FSM ACTIVITY")
+    print("user_message")
+    print(user_message)
+    # Make a completely new entry
+    if fsm_check.data == []:
+        if type == 'addition':
+            math_quiz_state_machine = MathQuizFSM()
+        else:
+            math_quiz_state_machine = MathSubtractionFSM()
+        messages = [math_quiz_state_machine.response_text]
+        dump_encoded = pickle_and_encode_state_machine(math_quiz_state_machine)
+
+        SUPA.table('state_machines').insert({
+            'contact_uuid': contact_uuid,
+            f'{type}': dump_encoded
+        }).execute()
+    # Update an existing record with a new state machine
+    elif not fsm_check.data[0][type]:
+        if type == 'addition':
+            math_quiz_state_machine = MathQuizFSM()
+        else:
+            math_quiz_state_machine = MathSubtractionFSM()
+        messages = [math_quiz_state_machine.response_text]
+        dump_encoded = pickle_and_encode_state_machine(math_quiz_state_machine)
+
+        SUPA.table('state_machines').update({
+            f'{type}': dump_encoded
+        }).eq(
+            "contact_uuid", contact_uuid
+        ).execute()      
+    # Update an existing record with an existing state machine
+    elif fsm_check.data[0][type]:
+        undump_encoded = base64.b64decode(
+            fsm_check.data[0][type].encode('utf-8')
+        )
+        math_quiz_state_machine = pickle.loads(undump_encoded)
+
+        math_quiz_state_machine.student_answer = user_message
+        math_quiz_state_machine.correct_answer = str(math_quiz_state_machine.correct_answer)
+        messages = math_quiz_state_machine.validate_answer()
+        dump_encoded = pickle_and_encode_state_machine(math_quiz_state_machine)          
+        SUPA.table('state_machines').update({
+            f'{type}': dump_encoded
+        }).eq(
+            "contact_uuid", contact_uuid
+        ).execute()
+    return messages
+
+
+def retrieve_microlesson_content(context_data, user_message, microlesson, contact_uuid):
+    if context_data['local_state'] == 'addition-question-sequence' or \
+        user_message == 'add' or \
+        microlesson == 'addition':
+        messages = manage_math_quiz_fsm(user_message, contact_uuid, 'addition')
+
+        if user_message == 'exit':
+            state_label = 'exit'
+        else:
+            state_label = 'addition-question-sequence'
+
+        input_prompt = messages.pop()
+        message_package = {
+            'messages': messages,
+            'input_prompt': input_prompt,
+            'state': state_label
+        }
+    elif context_data['local_state'] == 'subtraction-question-sequence' or \
+        user_message == 'subtract' or \
+        microlesson == 'subtraction':
+        messages = manage_math_quiz_fsm(user_message, contact_uuid, 'subtraction')
+
+        if user_message == 'exit':
+            state_label = 'exit'
+        else:
+            state_label = 'subtraction-question-sequence'
+
+        input_prompt = messages.pop()
+
+        message_package = {
+            'messages': messages,
+            'input_prompt': input_prompt,
+            'state': state_label
+        }
+    print("MICROLESSON CONTENT RESPONSE")
+    print(message_package)
+    return message_package
+
+
+curriculum_lookup_table = {
+    'N1.1.1_G1': 'addition',
+    'N1.1.1_G2': 'subtraction'
+}
+
+
+def lookup_local_state(next_state):
+    microlesson = curriculum_lookup_table[next_state]
+    return microlesson
+
+
+def manage_conversation_response(data_json):
+    """ Calls functions necessary to determine message and context data """
+    print("V2 ENDPOINT")
+
+    user_message = ''
+
+    # nlu_response = evaluate_message_with_nlu(message_data)
+
+    context_data = {
+        'contact_uuid': 'abcdefg',
+        'current_state': 'N1.1.1_G2',
+        'user_message': '1',
+        'local_state': ''
+    }
+    print("STEP 1")
+    if not context_data['current_state']:
+        context_data['current_state'] = 'N1.1.1_G1'
+
+    curriculum_copy = copy.deepcopy(gsm.curriculum)
+
+    print("STEP 2")
+    if context_data['user_message'] == 'easier':
+        curriculum_copy.left()
+        next_state = curriculum_copy.state
+    elif context_data['user_message'] == 'harder':
+        curriculum_copy.right()
+        next_state = curriculum_copy.state
+    else:
+        next_state = context_data['current_state']
+
+    print("STEP 3")
+    microlesson = lookup_local_state(next_state)
+
+    print("microlesson")
+    print(microlesson)
+
+    microlesson_content = retrieve_microlesson_content(context_data, context_data['user_message'], microlesson, context_data['contact_uuid'])
+
+    print("STEP 4")
+    # combine microlesson content and context_data object
+    return context_data

requirements.txt

@@ -4,6 +4,7 @@ fuzzywuzzy
 jsonpickle
 mathtext @ git+https://gitlab.com/tangibleai/community/mathtext@main
 fastapi==0.74.*
+openpyxl
 pydantic==1.10.*
 python-Levenshtein
 requests==2.27.*

scripts/make_request.py

@@ -69,12 +69,20 @@ def run_simulated_request(endpoint, sample_answer, context=None):
 # run_simulated_request('nlu', 'eight, nine, ten')
 # run_simulated_request('nlu', '8, 9, 10')
 # run_simulated_request('nlu', '8')
+<<<<<<< HEAD
 run_simulated_request('nlu', "I don't know")
+=======
+# run_simulated_request('nlu', "I don't know")
+>>>>>>> feature-wormhole
 # run_simulated_request('nlu', "I don't know eight")
 # run_simulated_request('nlu', "I don't 9")
 # run_simulated_request('nlu', "0.2")
 # run_simulated_request('nlu', 'Today is a wonderful day')
 # run_simulated_request('nlu', 'IDK 5?')
+<<<<<<< HEAD
+=======
+run_simulated_request('v2/manager', '')
+>>>>>>> feature-wormhole
 # run_simulated_request('manager', '')
 # run_simulated_request('manager', 'add')
 # run_simulated_request('manager', 'subtract')