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import json
import requests
def add_message_text_to_sample_object(message_text):
"""
Builds a sample request object using an example of a student answer
Input
- message_text: str - an example of user input to test
Example Input
"test message"
Output
- b_string: json b-string - simulated Turn.io message data
Example Output
b'{"context": "hi", "message_data": {"author_id": "+57787919091", "author_type": "OWNER", "contact_uuid": "j43hk26-2hjl-43jk-hnk2-k4ljl46j0ds09", "message_body": "test message", "message_direction": "inbound", "message_id": "4kl209sd0-a7b8-2hj3-8563-3hu4a89b32", "message_inserted_at": "2023-01-10T02:37:28.477940Z", "message_updated_at": "2023-01-10T02:37:28.487319Z"}}'
"""
message_data = '{' + f'"author_id": "+57787919091", "author_type": "OWNER", "contact_uuid": "j43hk26-2hjl-43jk-hnk2-k4ljl46j0ds09", "message_body": "{message_text}", "message_direction": "inbound", "message_id": "4kl209sd0-a7b8-2hj3-8563-3hu4a89b32", "message_inserted_at": "2023-01-10T02:37:28.477940Z", "message_updated_at": "2023-01-10T02:37:28.487319Z"' + '}'
# context_data = '{' + '"user":"", "state":"addition-question-sequence", "bot_message":"", "user_message":"{message_text}"' + '}'
context_data = '{' + '"user":"", "state":"start-conversation", "bot_message":"", "user_message":"{message_text}"' + '}'
# context_data = '{' + '"user":"", "state":"addition-question-sequence", "bot_message":"", "user_message":"{message_text}","text": "What is 2+3?","question_numbers": [4,3],"right_answer": 7,"number_correct": 2, "number_incorrect": 0, "hints_used": 0, "level": "easy"' + '}'
json_string = '{' + f'"context_data": {context_data}, "message_data": {message_data}' + '}'
b_string = json_string.encode("utf-8")
return b_string
# """
# "text": "What is 2+3?",
# "question_numbers": [2,3],
# "right_answer": 5,
# "number_correct": 2,
# "hints_used": 0,
# """
def run_simulated_request(endpoint, sample_answer, context=None):
print(f"Case: {sample_answer}")
b_string = add_message_text_to_sample_object(sample_answer)
if endpoint == 'sentiment-analysis' or endpoint == 'text2int':
request = requests.post(
url=f'http://localhost:7860/{endpoint}',
json={'content': sample_answer}
).json()
else:
request = requests.post(
url=f'http://localhost:7860/{endpoint}',
data=b_string
).json()
print(request)
# run_simulated_request('sentiment-analysis', 'I reject it')
# run_simulated_request('text2int', 'seven thousand nine hundred fifty seven')
run_simulated_request('nlu', 'test message')
run_simulated_request('nlu', 'eight')
run_simulated_request('nlu', 'is it 8')
run_simulated_request('nlu', 'can I know how its 0.5')
run_simulated_request('nlu', 'eight, nine, ten')
run_simulated_request('nlu', '8, 9, 10')
run_simulated_request('nlu', '8')
run_simulated_request('nlu', "I don't know")
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?')
# run_simulated_request('manager', '')
# run_simulated_request('manager', 'add')
# run_simulated_request('manager', 'subtract')
run_simulated_request("start", {
'difficulty': 0.69,
'do_increase': True
})
run_simulated_request("hint", {
'start': 2,
'step': 1,
'difficulty': 0.01 # optional
})
run_simulated_request("question", {
'start': 2,
'step': 1,
'question_num': 2 # optional
})
run_simulated_request("difficulty", {
'difficulty': 0.01,
'do_increase': True # True | False
})
run_simulated_request("start_step", {
'start': 2,
'step': 1,
'difficulty': 0.01 # optional
})
run_simulated_request("sequence", {
'start': 2,
'step': 1,
'sep': '... '
})
# run_simulated_request('manager', 'exit')
# Example of simplified object received from Turn.io stacks
# This is a contrived example to show the structure, not an actual state
# NOTE: This is actually a bstring, not a dict
simplified_json = {
"context": {
"user": "+57787919091",
"state": "answer-addition-problem",
"bot_message": "What is 2+2?",
"user_message": "eight",
"type": "ask"
},
"message_data": {
"author_id": "+57787919091",
"author_type": "OWNER",
"contact_uuid": "j43hk26-2hjl-43jk-hnk2-k4ljl46j0ds09",
"message_body": "eight",
"message_direction": "inbound",
"message_id": "4kl209sd0-a7b8-2hj3-8563-3hu4a89b32",
"message_inserted_at": "2023-01-10T02:37:28.477940Z",
"message_updated_at": "2023-01-10T02:37:28.487319Z"
}
}
# Full example of event data from Turn.io
# simplified_json is built from this in Turn.io
# full_json = {
# 'message': {
# '_vnd': {
# 'v1': {
# 'author': {
# 'id': 57787919091,
# 'name': 'GT',
# 'type': 'OWNER'
# },
# 'card_uuid': None,
# 'chat': {
# 'assigned_to': {
# 'id': 'jhk151kl-hj42-3752-3hjk-h4jk6hjkk2',
# 'name': 'Greg Thompson',
# 'type': 'OPERATOR'
# },
# 'contact_uuid': 'j43hk26-2hjl-43jk-hnk2-k4ljl46j0ds09',
# 'inserted_at': '2022-07-05T04:00:34.033522Z',
# 'owner': '+57787919091',
# 'permalink': 'https://app.turn.io/c/4kl209sd0-a7b8-2hj3-8563-3hu4a89b32',
# 'state': 'OPEN',
# 'state_reason': 'Re-opened by inbound message.',
# 'unread_count': 19,
# 'updated_at': '2023-01-10T02:37:28.487319Z',
# 'uuid': '4kl209sd0-a7b8-2hj3-8563-3hu4a89b32'
# },
# 'direction': 'inbound',
# 'faq_uuid': None,
# 'in_reply_to': None,
# 'inserted_at': '2023-01-10T02:37:28.477940Z',
# 'labels': [{
# 'confidence': 0.506479332,
# 'metadata': {
# 'nlu': {
# 'confidence': 0.506479332,
# 'intent': 'question',
# 'model_name': 'nlu-general-spacy-ngrams-20191014'
# }
# },
# 'uuid': 'ha7890s2k-hjk2-2476-s8d9-fh9779a8a9ds',
# 'value': 'Unclassified'
# }],
# 'last_status': None,
# 'last_status_timestamp': None,
# 'on_fallback_channel': False,
# 'rendered_content': None,
# 'uuid': 's8df79zhws-h89s-hj23-7s8d-thb248d9bh2qn'
# }
# },
# 'from': 57787919091,
# 'id': 'hsjkthzZGehkzs09sijWA3',
# 'text': {'body': 'eight'},
# 'timestamp': 1673318248,
# 'type': 'text'
# },
# 'type': 'message'
# }
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