Initial Query

Given a parse function like def parse_transcript(content): transcript_segments = [] pattern = r'\[(\d{2}:\d{2}:\d{2}\.\d{3}) --> (\d{2}:\d{2}:\d{2}\.\d{3})\] (.*)' matches = re.findall(pattern, content) for start_time, end_time, text in matches: start_seconds = timedelta(hours=int(start_time[:2]), minutes=int(start_time[3:5]), seconds=int(start_time[6:8]), milliseconds=int(start_time[9:])).total_seconds() end_seconds = timedelta(hours=int(end_time[:2]), minutes=int(end_time[3:5]), seconds=int(end_time[6:8]), milliseconds=int(end_time[9:])).total_seconds() transcript_segments.append((start_seconds, end_seconds, text)) return transcript_segments for data like [00:00:14.240 --> 00:00:14.420] the [00:00:14.420 --> 00:00:14.860] robust [00:00:14.860 --> 00:00:15.020] ness [00:00:15.020 --> 00:00:15.140] of [00:00:15.140 --> 00:00:15.500] neural [00:00:15.500 --> 00:00:15.870] networks [00:00:15.870 --> 00:00:16.200] . [00:00:16.200 --> 00:00:16.410] And [00:00:16.410 --> 00:00:16.700] this [00:00:16.700 --> 00:00:16.840] is [00:00:16.840 --> 00:00:17.200] joint write a merge() function that (1) calls parse and (2) merges words into sentences that end in period. Start with the first word and end with the period. Return a list of strings.

LLM Generation

Query

Given a parse function like def parse_transcript(content): transcript_segments = [] pattern = r'\[(\d{2}:\d{2}:\d{2}\.\d{3}) --> (\d{2}:\d{2}:\d{2}\.\d{3})\] (.*)' matches = re.findall(pattern, content) for start_time, end_time, text in matches: start_seconds = timedelta(hours=int(start_time[:2]), minutes=int(start_time[3:5]), seconds=int(start_time[6:8]), milliseconds=int(start_time[9:])).total_seconds() end_seconds = timedelta(hours=int(end_time[:2]), minutes=int(end_time[3:5]), seconds=int(end_time[6:8]), milliseconds=int(end_time[9:])).total_seconds() transcript_segments.append((start_seconds, end_seconds, text)) return transcript_segments for data like [00:00:14.240 --> 00:00:14.420] the [00:00:14.420 --> 00:00:14.860] robust [00:00:14.860 --> 00:00:15.020] ness [00:00:15.020 --> 00:00:15.140] of [00:00:15.140 --> 00:00:15.500] neural [00:00:15.500 --> 00:00:15.870] networks [00:00:15.870 --> 00:00:16.200] . [00:00:16.200 --> 00:00:16.410] And [00:00:16.410 --> 00:00:16.700] this [00:00:16.700 --> 00:00:16.840] is [00:00:16.840 --> 00:00:17.200] joint write a merge() function that (1) calls parse and (2) merges words into sentences that end in period. Start with the first word and end with the period. Return a list of strings.

Output

Here is the merge() function: 

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import re
from datetime import timedelta

def parse_transcript(content):
    transcript_segments = []
    pattern = r'\[(\d{2}:\d{2}:\d{2}\.\d{3}) --> (\d{2}:\d{2}:\d{2}\.\d{3})\]  (.*)'
    matches = re.findall(pattern, content)

    for start_time, end_time, text in matches:
        start_seconds = timedelta(hours=int(start_time[:2]), minutes=int(start_time[3:5]), seconds=int(start_time[6:8]), milliseconds=int(start_time[9:])).total_seconds()
        end_seconds = timedelta(hours=int(end_time[:2]), minutes=int(end_time[3:5]), seconds=int(end_time[6:8]), milliseconds=int(end_time[9:])).total_seconds()
        transcript_segments.append((start_seconds, end_seconds, text))

    return transcript_segments

def merge(content):
    transcript_segments = parse_transcript(content)
    sentences = []
    current_sentence = ""

    for segment in transcript_segments:
        text = segment[2]
        current_sentence += text.strip()
        
        if text.strip().endswith('.'):
            sentences.append(current_sentence)
            current_sentence = ""
    
    if current_sentence:
        sentences.append(current_sentence)

    return sentences

# Example usage
content = '''
[00:00:14.240 --> 00:00:14.420]   the
[00:00:14.420 --> 00:00:14.860]   robust
[00:00:14.860 --> 00:00:15.020]  ness
[00:00:15.020 --> 00:00:15.140]   of
[00:00:15.140 --> 00:00:15.500]   neural
[00:00:15.500 --> 00:00:15.870]   networks
[00:00:15.870 --> 00:00:16.200]  .
[00:00:16.200 --> 00:00:16.410]   And
[00:00:16.410 --> 00:00:16.700]   this
[00:00:16.700 --> 00:00:16.840]   is
[00:00:16.840 --> 00:00:17.200]   joint
'''
sentences = merge(content)
for sentence in sentences:
    print(sentence)
This merge() function will merge words into sentences that end with a period and return a list of strings.

Extract Code

I extracted the following code from that output: 

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import re
from datetime import timedelta

def parse_transcript(content):
    transcript_segments = []
    pattern = r'\[(\d{2}:\d{2}:\d{2}\.\d{3}) --> (\d{2}:\d{2}:\d{2}\.\d{3})\]  (.*)'
    matches = re.findall(pattern, content)

    for start_time, end_time, text in matches:
        start_seconds = timedelta(hours=int(start_time[:2]), minutes=int(start_time[3:5]), seconds=int(start_time[6:8]), milliseconds=int(start_time[9:])).total_seconds()
        end_seconds = timedelta(hours=int(end_time[:2]), minutes=int(end_time[3:5]), seconds=int(end_time[6:8]), milliseconds=int(end_time[9:])).total_seconds()
        transcript_segments.append((start_seconds, end_seconds, text))

    return transcript_segments

def merge(content):
    transcript_segments = parse_transcript(content)
    sentences = []
    current_sentence = ""

    for segment in transcript_segments:
        text = segment[2]
        current_sentence += text.strip()
        
        if text.strip().endswith('.'):
            sentences.append(current_sentence)
            current_sentence = ""
    
    if current_sentence:
        sentences.append(current_sentence)

    return sentences

# Example usage
content = '''
[00:00:14.240 --> 00:00:14.420]   the
[00:00:14.420 --> 00:00:14.860]   robust
[00:00:14.860 --> 00:00:15.020]  ness
[00:00:15.020 --> 00:00:15.140]   of
[00:00:15.140 --> 00:00:15.500]   neural
[00:00:15.500 --> 00:00:15.870]   networks
[00:00:15.870 --> 00:00:16.200]  .
[00:00:16.200 --> 00:00:16.410]   And
[00:00:16.410 --> 00:00:16.700]   this
[00:00:16.700 --> 00:00:16.840]   is
[00:00:16.840 --> 00:00:17.200]   joint
'''
sentences = merge(content)
for sentence in sentences:
    print(sentence)

Run Code Interpreter

Running the following program: 

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import re
from datetime import timedelta

def parse_transcript(content):
    transcript_segments = []
    pattern = r'\[(\d{2}:\d{2}:\d{2}\.\d{3}) --> (\d{2}:\d{2}:\d{2}\.\d{3})\]  (.*)'
    matches = re.findall(pattern, content)

    for start_time, end_time, text in matches:
        start_seconds = timedelta(hours=int(start_time[:2]), minutes=int(start_time[3:5]), seconds=int(start_time[6:8]), milliseconds=int(start_time[9:])).total_seconds()
        end_seconds = timedelta(hours=int(end_time[:2]), minutes=int(end_time[3:5]), seconds=int(end_time[6:8]), milliseconds=int(end_time[9:])).total_seconds()
        transcript_segments.append((start_seconds, end_seconds, text))

    return transcript_segments

def merge(content):
    transcript_segments = parse_transcript(content)
    sentences = []
    current_sentence = ""

    for segment in transcript_segments:
        text = segment[2]
        current_sentence += text.strip()
        
        if text.strip().endswith('.'):
            sentences.append(current_sentence)
            current_sentence = ""
    
    if current_sentence:
        sentences.append(current_sentence)

    return sentences

# Example usage
content = '''
[00:00:14.240 --> 00:00:14.420]   the
[00:00:14.420 --> 00:00:14.860]   robust
[00:00:14.860 --> 00:00:15.020]  ness
[00:00:15.020 --> 00:00:15.140]   of
[00:00:15.140 --> 00:00:15.500]   neural
[00:00:15.500 --> 00:00:15.870]   networks
[00:00:15.870 --> 00:00:16.200]  .
[00:00:16.200 --> 00:00:16.410]   And
[00:00:16.410 --> 00:00:16.700]   this
[00:00:16.700 --> 00:00:16.840]   is
[00:00:16.840 --> 00:00:17.200]   joint
'''
sentences = merge(content)
for sentence in sentences:
    print(sentence)




def parse_transcript(content):
    transcript_segments = []
    pattern = r'\[(\d{2}:\d{2}:\d{2}\.\d{3}) --> (\d{2}:\d{2}:\d{2}\.\d{3})\]  (.*)'
    matches = re.findall(pattern, content)

    for start_time, end_time, text in matches:
        start_seconds = timedelta(hours=int(start_time[:2]), minutes=int(start_time[3:5]), seconds=int(start_time[6:8]), milliseconds=int(start_time[9:])).total_seconds()
        end_seconds = timedelta(hours=int(end_time[:2]), minutes=int(end_time[3:5]), seconds=int(end_time[6:8]), milliseconds=int(end_time[9:])).total_seconds()
        transcript_segments.append((start_seconds, end_seconds, text))

    return transcript_segments


answer = merge("[00:00:14.240 --> 00:00:14.420]   the\n[00:00:14.420 --> 00:00:14.860]   robust\n[00:00:14.860 --> 00:00:15.020]  ness\n[00:00:15.020 --> 00:00:15.140]   of\n[00:00:15.140 --> 00:00:15.500]   neural\n[00:00:15.500 --> 00:00:15.870]   networks\n[00:00:15.870 --> 00:00:16.200]  .\n[00:00:16.200 --> 00:00:16.410]   And\n[00:00:16.410 --> 00:00:16.700]   this\n[00:00:16.700 --> 00:00:16.840]   is\n[00:00:16.840 --> 00:00:17.200]   joint\n")
expected = [' the robustness of neural networks.', ' And this is joint']
assert answer == expected, f'Wrong answer; got {answer} instead of {expected}'
print('All tests passed')
And got the output: therobustnessofneuralnetworks. Andthisisjoint Traceback (most recent call last): File "/usr/src/app/main.py", line 71, in <module> assert answer == expected, f'Wrong answer; got {answer} instead of {expected}' ^^^^^^^^^^^^^^^^^^ AssertionError: Wrong answer; got ['therobustnessofneuralnetworks.', 'Andthisisjoint'] instead of [' the robustness of neural networks.', ' And this is joint']

Substring Evaluation

Testing if the previous output contains the string All tests passed: False

Initial Query

Given a parse function like def parse_transcript(content): transcript_segments = [] pattern = r'\[(\d{2}:\d{2}:\d{2}\.\d{3}) --> (\d{2}:\d{2}:\d{2}\.\d{3})\] (.*)' matches = re.findall(pattern, content) for start_time, end_time, text in matches: start_seconds = timedelta(hours=int(start_time[:2]), minutes=int(start_time[3:5]), seconds=int(start_time[6:8]), milliseconds=int(start_time[9:])).total_seconds() end_seconds = timedelta(hours=int(end_time[:2]), minutes=int(end_time[3:5]), seconds=int(end_time[6:8]), milliseconds=int(end_time[9:])).total_seconds() transcript_segments.append((start_seconds, end_seconds, text)) return transcript_segments for data like [00:00:14.240 --> 00:00:14.420] the [00:00:14.420 --> 00:00:14.860] robust [00:00:14.860 --> 00:00:15.020] ness [00:00:15.020 --> 00:00:15.140] of [00:00:15.140 --> 00:00:15.500] neural [00:00:15.500 --> 00:00:15.870] networks [00:00:15.870 --> 00:00:16.200] . [00:00:16.200 --> 00:00:16.410] And [00:00:16.410 --> 00:00:16.700] this [00:00:16.700 --> 00:00:16.840] is [00:00:16.840 --> 00:00:17.200] joint write a merge() function that (1) calls parse and (2) merges words into sentences that end in period. Start with the first word and end with the period. Return a list of strings.

LLM Generation

Query

Given a parse function like def parse_transcript(content): transcript_segments = [] pattern = r'\[(\d{2}:\d{2}:\d{2}\.\d{3}) --> (\d{2}:\d{2}:\d{2}\.\d{3})\] (.*)' matches = re.findall(pattern, content) for start_time, end_time, text in matches: start_seconds = timedelta(hours=int(start_time[:2]), minutes=int(start_time[3:5]), seconds=int(start_time[6:8]), milliseconds=int(start_time[9:])).total_seconds() end_seconds = timedelta(hours=int(end_time[:2]), minutes=int(end_time[3:5]), seconds=int(end_time[6:8]), milliseconds=int(end_time[9:])).total_seconds() transcript_segments.append((start_seconds, end_seconds, text)) return transcript_segments for data like [00:00:14.240 --> 00:00:14.420] the [00:00:14.420 --> 00:00:14.860] robust [00:00:14.860 --> 00:00:15.020] ness [00:00:15.020 --> 00:00:15.140] of [00:00:15.140 --> 00:00:15.500] neural [00:00:15.500 --> 00:00:15.870] networks [00:00:15.870 --> 00:00:16.200] . [00:00:16.200 --> 00:00:16.410] And [00:00:16.410 --> 00:00:16.700] this [00:00:16.700 --> 00:00:16.840] is [00:00:16.840 --> 00:00:17.200] joint write a merge() function that (1) calls parse and (2) merges words into sentences that end in period. Start with the first word and end with the period. Return a list of strings.

Output

Here is the implementation of the merge function: 

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import re
from datetime import timedelta

def parse_transcript(content):
    transcript_segments = []
    pattern = r'\[(\d{2}:\d{2}:\d{2}\.\d{3}) --> (\d{2}:\d{2}:\d{2}\.\d{3})\]  (.*)'
    matches = re.findall(pattern, content)

    for start_time, end_time, text in matches:
        start_seconds = timedelta(hours=int(start_time[:2]), minutes=int(start_time[3:5]), seconds=int(start_time[6:8]), milliseconds=int(start_time[9:])).total_seconds()
        end_seconds = timedelta(hours=int(end_time[:2]), minutes=int(end_time[3:5]), seconds=int(end_time[6:8]), milliseconds=int(end_time[9:])).total_seconds()
        transcript_segments.append((start_seconds, end_seconds, text))

    return transcript_segments

def merge(content):
    transcript_segments = parse_transcript(content)
    sentences = []
    current_sentence = ""
    
    for segment in transcript_segments:
        text = segment[2].strip()
        if text.endswith("."):
            current_sentence += text
            sentences.append(current_sentence)
            current_sentence = ""
        else:
            current_sentence += text + " "

    return sentences

# Example usage
content = '''
[00:00:14.240 --> 00:00:14.420]   the
[00:00:14.420 --> 00:00:14.860]   robust
[00:00:14.860 --> 00:00:15.020]  ness
[00:00:15.020 --> 00:00:15.140]   of
[00:00:15.140 --> 00:00:15.500]   neural
[00:00:15.500 --> 00:00:15.870]   networks
[00:00:15.870 --> 00:00:16.200]  .
[00:00:16.200 --> 00:00:16.410]   And
[00:00:16.410 --> 00:00:16.700]   this
[00:00:16.700 --> 00:00:16.840]   is
[00:00:16.840 --> 00:00:17.200]   joint
'''

sentences = merge(content)
for sentence in sentences:
    print(sentence)
This merge function first calls the parse_transcript function to extract the transcript segments and then merges the words into sentences that end with a period. The resulting list of sentences is returned.

Extract Code

I extracted the following code from that output: 

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import re
from datetime import timedelta

def parse_transcript(content):
    transcript_segments = []
    pattern = r'\[(\d{2}:\d{2}:\d{2}\.\d{3}) --> (\d{2}:\d{2}:\d{2}\.\d{3})\]  (.*)'
    matches = re.findall(pattern, content)

    for start_time, end_time, text in matches:
        start_seconds = timedelta(hours=int(start_time[:2]), minutes=int(start_time[3:5]), seconds=int(start_time[6:8]), milliseconds=int(start_time[9:])).total_seconds()
        end_seconds = timedelta(hours=int(end_time[:2]), minutes=int(end_time[3:5]), seconds=int(end_time[6:8]), milliseconds=int(end_time[9:])).total_seconds()
        transcript_segments.append((start_seconds, end_seconds, text))

    return transcript_segments

def merge(content):
    transcript_segments = parse_transcript(content)
    sentences = []
    current_sentence = ""
    
    for segment in transcript_segments:
        text = segment[2].strip()
        if text.endswith("."):
            current_sentence += text
            sentences.append(current_sentence)
            current_sentence = ""
        else:
            current_sentence += text + " "

    return sentences

# Example usage
content = '''
[00:00:14.240 --> 00:00:14.420]   the
[00:00:14.420 --> 00:00:14.860]   robust
[00:00:14.860 --> 00:00:15.020]  ness
[00:00:15.020 --> 00:00:15.140]   of
[00:00:15.140 --> 00:00:15.500]   neural
[00:00:15.500 --> 00:00:15.870]   networks
[00:00:15.870 --> 00:00:16.200]  .
[00:00:16.200 --> 00:00:16.410]   And
[00:00:16.410 --> 00:00:16.700]   this
[00:00:16.700 --> 00:00:16.840]   is
[00:00:16.840 --> 00:00:17.200]   joint
'''

sentences = merge(content)
for sentence in sentences:
    print(sentence)

Run Code Interpreter

Running the following program: 

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import re
from datetime import timedelta

def parse_transcript(content):
    transcript_segments = []
    pattern = r'\[(\d{2}:\d{2}:\d{2}\.\d{3}) --> (\d{2}:\d{2}:\d{2}\.\d{3})\]  (.*)'
    matches = re.findall(pattern, content)

    for start_time, end_time, text in matches:
        start_seconds = timedelta(hours=int(start_time[:2]), minutes=int(start_time[3:5]), seconds=int(start_time[6:8]), milliseconds=int(start_time[9:])).total_seconds()
        end_seconds = timedelta(hours=int(end_time[:2]), minutes=int(end_time[3:5]), seconds=int(end_time[6:8]), milliseconds=int(end_time[9:])).total_seconds()
        transcript_segments.append((start_seconds, end_seconds, text))

    return transcript_segments

def merge(content):
    transcript_segments = parse_transcript(content)
    sentences = []
    current_sentence = ""
    
    for segment in transcript_segments:
        text = segment[2].strip()
        if text.endswith("."):
            current_sentence += text
            sentences.append(current_sentence)
            current_sentence = ""
        else:
            current_sentence += text + " "

    return sentences

# Example usage
content = '''
[00:00:14.240 --> 00:00:14.420]   the
[00:00:14.420 --> 00:00:14.860]   robust
[00:00:14.860 --> 00:00:15.020]  ness
[00:00:15.020 --> 00:00:15.140]   of
[00:00:15.140 --> 00:00:15.500]   neural
[00:00:15.500 --> 00:00:15.870]   networks
[00:00:15.870 --> 00:00:16.200]  .
[00:00:16.200 --> 00:00:16.410]   And
[00:00:16.410 --> 00:00:16.700]   this
[00:00:16.700 --> 00:00:16.840]   is
[00:00:16.840 --> 00:00:17.200]   joint
'''

sentences = merge(content)
for sentence in sentences:
    print(sentence)




def parse_transcript(content):
    transcript_segments = []
    pattern = r'\[(\d{2}:\d{2}:\d{2}\.\d{3}) --> (\d{2}:\d{2}:\d{2}\.\d{3})\]  (.*)'
    matches = re.findall(pattern, content)

    for start_time, end_time, text in matches:
        start_seconds = timedelta(hours=int(start_time[:2]), minutes=int(start_time[3:5]), seconds=int(start_time[6:8]), milliseconds=int(start_time[9:])).total_seconds()
        end_seconds = timedelta(hours=int(end_time[:2]), minutes=int(end_time[3:5]), seconds=int(end_time[6:8]), milliseconds=int(end_time[9:])).total_seconds()
        transcript_segments.append((start_seconds, end_seconds, text))

    return transcript_segments


answer = merge("[00:00:14.240 --> 00:00:14.420]   the\n[00:00:14.420 --> 00:00:14.860]   robust\n[00:00:14.860 --> 00:00:15.020]  ness\n[00:00:15.020 --> 00:00:15.140]   of\n[00:00:15.140 --> 00:00:15.500]   neural\n[00:00:15.500 --> 00:00:15.870]   networks\n[00:00:15.870 --> 00:00:16.200]  .\n[00:00:16.200 --> 00:00:16.410]   And\n[00:00:16.410 --> 00:00:16.700]   this\n[00:00:16.700 --> 00:00:16.840]   is\n[00:00:16.840 --> 00:00:17.200]   joint\n")
expected = [' the robustness of neural networks.', ' And this is joint']
assert answer == expected, f'Wrong answer; got {answer} instead of {expected}'
print('All tests passed')
And got the output: the robust ness of neural networks . Traceback (most recent call last): File "/usr/src/app/main.py", line 70, in <module> assert answer == expected, f'Wrong answer; got {answer} instead of {expected}' ^^^^^^^^^^^^^^^^^^ AssertionError: Wrong answer; got ['the robust ness of neural networks .'] instead of [' the robustness of neural networks.', ' And this is joint']

Substring Evaluation

Testing if the previous output contains the string All tests passed: False

Initial Query

Given a parse function like def parse_transcript(content): transcript_segments = [] pattern = r'\[(\d{2}:\d{2}:\d{2}\.\d{3}) --> (\d{2}:\d{2}:\d{2}\.\d{3})\] (.*)' matches = re.findall(pattern, content) for start_time, end_time, text in matches: start_seconds = timedelta(hours=int(start_time[:2]), minutes=int(start_time[3:5]), seconds=int(start_time[6:8]), milliseconds=int(start_time[9:])).total_seconds() end_seconds = timedelta(hours=int(end_time[:2]), minutes=int(end_time[3:5]), seconds=int(end_time[6:8]), milliseconds=int(end_time[9:])).total_seconds() transcript_segments.append((start_seconds, end_seconds, text)) return transcript_segments for data like [00:00:14.240 --> 00:00:14.420] the [00:00:14.420 --> 00:00:14.860] robust [00:00:14.860 --> 00:00:15.020] ness [00:00:15.020 --> 00:00:15.140] of [00:00:15.140 --> 00:00:15.500] neural [00:00:15.500 --> 00:00:15.870] networks [00:00:15.870 --> 00:00:16.200] . [00:00:16.200 --> 00:00:16.410] And [00:00:16.410 --> 00:00:16.700] this [00:00:16.700 --> 00:00:16.840] is [00:00:16.840 --> 00:00:17.200] joint write a merge() function that (1) calls parse and (2) merges words into sentences that end in period. Start with the first word and end with the period. Return a list of strings.

LLM Generation

Query

Given a parse function like def parse_transcript(content): transcript_segments = [] pattern = r'\[(\d{2}:\d{2}:\d{2}\.\d{3}) --> (\d{2}:\d{2}:\d{2}\.\d{3})\] (.*)' matches = re.findall(pattern, content) for start_time, end_time, text in matches: start_seconds = timedelta(hours=int(start_time[:2]), minutes=int(start_time[3:5]), seconds=int(start_time[6:8]), milliseconds=int(start_time[9:])).total_seconds() end_seconds = timedelta(hours=int(end_time[:2]), minutes=int(end_time[3:5]), seconds=int(end_time[6:8]), milliseconds=int(end_time[9:])).total_seconds() transcript_segments.append((start_seconds, end_seconds, text)) return transcript_segments for data like [00:00:14.240 --> 00:00:14.420] the [00:00:14.420 --> 00:00:14.860] robust [00:00:14.860 --> 00:00:15.020] ness [00:00:15.020 --> 00:00:15.140] of [00:00:15.140 --> 00:00:15.500] neural [00:00:15.500 --> 00:00:15.870] networks [00:00:15.870 --> 00:00:16.200] . [00:00:16.200 --> 00:00:16.410] And [00:00:16.410 --> 00:00:16.700] this [00:00:16.700 --> 00:00:16.840] is [00:00:16.840 --> 00:00:17.200] joint write a merge() function that (1) calls parse and (2) merges words into sentences that end in period. Start with the first word and end with the period. Return a list of strings.

Output

import re from datetime import timedelta def parse_transcript(content): transcript_segments = [] pattern = r'\[(\d{2}:\d{2}:\d{2}\.\d{3}) --> (\d{2}:\d{2}:\d{2}\.\d{3})\] (.*)' matches = re.findall(pattern, content) for start_time, end_time, text in matches: start_seconds = timedelta(hours=int(start_time[:2]), minutes=int(start_time[3:5]), seconds=int(start_time[6:8]), milliseconds=int(start_time[9:])).total_seconds() end_seconds = timedelta(hours=int(end_time[:2]), minutes=int(end_time[3:5]), seconds=int(end_time[6:8]), milliseconds=int(end_time[9:])).total_seconds() transcript_segments.append((start_seconds, end_seconds, text)) return transcript_segments def merge(content): transcript_segments = parse_transcript(content) sentences = [] current_sentence = "" for segment in transcript_segments: text = segment[2] if text.endswith("."): current_sentence += text sentences.append(current_sentence) current_sentence = "" else: current_sentence += text return sentences content = """ [00:00:14.240 --> 00:00:14.420] the [00:00:14.420 --> 00:00:14.860] robust [00:00:14.860 --> 00:00:15.020] ness [00:00:15.020 --> 00:00:15.140] of [00:00:15.140 --> 00:00:15.500] neural [00:00:15.500 --> 00:00:15.870] networks [00:00:15.870 --> 00:00:16.200] . [00:00:16.200 --> 00:00:16.410] And [00:00:16.410 --> 00:00:16.700] this [00:00:16.700 --> 00:00:16.840] is [00:00:16.840 --> 00:00:17.200] joint """ sentences = merge(content) for sentence in sentences: print(sentence)

Extract Code

I extracted the following code from that output: 

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import re
from datetime import timedelta

def parse_transcript(content):
    transcript_segments = []
    pattern = r'\[(\d{2}:\d{2}:\d{2}\.\d{3}) --> (\d{2}:\d{2}:\d{2}\.\d{3})\]  (.*)'
    matches = re.findall(pattern, content)

    for start_time, end_time, text in matches:
        start_seconds = timedelta(hours=int(start_time[:2]), minutes=int(start_time[3:5]), seconds=int(start_time[6:8]), milliseconds=int(start_time[9:])).total_seconds()
        end_seconds = timedelta(hours=int(end_time[:2]), minutes=int(end_time[3:5]), seconds=int(end_time[6:8]), milliseconds=int(end_time[9:])).total_seconds()
        transcript_segments.append((start_seconds, end_seconds, text))

    return transcript_segments

def merge(content):
    transcript_segments = parse_transcript(content)
    sentences = []
    current_sentence = ""

    for segment in transcript_segments:
        text = segment[2]
        if text.endswith("."):
            current_sentence += text
            sentences.append(current_sentence)
            current_sentence = ""
        else:
            current_sentence += text

    return sentences

Run Code Interpreter

Running the following program: 

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import re
from datetime import timedelta

def parse_transcript(content):
    transcript_segments = []
    pattern = r'\[(\d{2}:\d{2}:\d{2}\.\d{3}) --> (\d{2}:\d{2}:\d{2}\.\d{3})\]  (.*)'
    matches = re.findall(pattern, content)

    for start_time, end_time, text in matches:
        start_seconds = timedelta(hours=int(start_time[:2]), minutes=int(start_time[3:5]), seconds=int(start_time[6:8]), milliseconds=int(start_time[9:])).total_seconds()
        end_seconds = timedelta(hours=int(end_time[:2]), minutes=int(end_time[3:5]), seconds=int(end_time[6:8]), milliseconds=int(end_time[9:])).total_seconds()
        transcript_segments.append((start_seconds, end_seconds, text))

    return transcript_segments

def merge(content):
    transcript_segments = parse_transcript(content)
    sentences = []
    current_sentence = ""

    for segment in transcript_segments:
        text = segment[2]
        if text.endswith("."):
            current_sentence += text
            sentences.append(current_sentence)
            current_sentence = ""
        else:
            current_sentence += text

    return sentences



def parse_transcript(content):
    transcript_segments = []
    pattern = r'\[(\d{2}:\d{2}:\d{2}\.\d{3}) --> (\d{2}:\d{2}:\d{2}\.\d{3})\]  (.*)'
    matches = re.findall(pattern, content)

    for start_time, end_time, text in matches:
        start_seconds = timedelta(hours=int(start_time[:2]), minutes=int(start_time[3:5]), seconds=int(start_time[6:8]), milliseconds=int(start_time[9:])).total_seconds()
        end_seconds = timedelta(hours=int(end_time[:2]), minutes=int(end_time[3:5]), seconds=int(end_time[6:8]), milliseconds=int(end_time[9:])).total_seconds()
        transcript_segments.append((start_seconds, end_seconds, text))

    return transcript_segments


answer = merge("[00:00:14.240 --> 00:00:14.420]   the\n[00:00:14.420 --> 00:00:14.860]   robust\n[00:00:14.860 --> 00:00:15.020]  ness\n[00:00:15.020 --> 00:00:15.140]   of\n[00:00:15.140 --> 00:00:15.500]   neural\n[00:00:15.500 --> 00:00:15.870]   networks\n[00:00:15.870 --> 00:00:16.200]  .\n[00:00:16.200 --> 00:00:16.410]   And\n[00:00:16.410 --> 00:00:16.700]   this\n[00:00:16.700 --> 00:00:16.840]   is\n[00:00:16.840 --> 00:00:17.200]   joint\n")
expected = [' the robustness of neural networks.', ' And this is joint']
assert answer == expected, f'Wrong answer; got {answer} instead of {expected}'
print('All tests passed')
And got the output: Traceback (most recent call last): File "/usr/src/app/main.py", line 49, in <module> assert answer == expected, f'Wrong answer; got {answer} instead of {expected}' ^^^^^^^^^^^^^^^^^^ AssertionError: Wrong answer; got [' the robustness of neural networks.'] instead of [' the robustness of neural networks.', ' And this is joint']

Substring Evaluation

Testing if the previous output contains the string All tests passed: False

Initial Query

Given a parse function like def parse_transcript(content): transcript_segments = [] pattern = r'\[(\d{2}:\d{2}:\d{2}\.\d{3}) --> (\d{2}:\d{2}:\d{2}\.\d{3})\] (.*)' matches = re.findall(pattern, content) for start_time, end_time, text in matches: start_seconds = timedelta(hours=int(start_time[:2]), minutes=int(start_time[3:5]), seconds=int(start_time[6:8]), milliseconds=int(start_time[9:])).total_seconds() end_seconds = timedelta(hours=int(end_time[:2]), minutes=int(end_time[3:5]), seconds=int(end_time[6:8]), milliseconds=int(end_time[9:])).total_seconds() transcript_segments.append((start_seconds, end_seconds, text)) return transcript_segments for data like [00:00:14.240 --> 00:00:14.420] the [00:00:14.420 --> 00:00:14.860] robust [00:00:14.860 --> 00:00:15.020] ness [00:00:15.020 --> 00:00:15.140] of [00:00:15.140 --> 00:00:15.500] neural [00:00:15.500 --> 00:00:15.870] networks [00:00:15.870 --> 00:00:16.200] . [00:00:16.200 --> 00:00:16.410] And [00:00:16.410 --> 00:00:16.700] this [00:00:16.700 --> 00:00:16.840] is [00:00:16.840 --> 00:00:17.200] joint write a merge() function that (1) calls parse and (2) merges words into sentences that end in period. Start with the first word and end with the period. Return a list of strings.

LLM Generation

Query

Given a parse function like def parse_transcript(content): transcript_segments = [] pattern = r'\[(\d{2}:\d{2}:\d{2}\.\d{3}) --> (\d{2}:\d{2}:\d{2}\.\d{3})\] (.*)' matches = re.findall(pattern, content) for start_time, end_time, text in matches: start_seconds = timedelta(hours=int(start_time[:2]), minutes=int(start_time[3:5]), seconds=int(start_time[6:8]), milliseconds=int(start_time[9:])).total_seconds() end_seconds = timedelta(hours=int(end_time[:2]), minutes=int(end_time[3:5]), seconds=int(end_time[6:8]), milliseconds=int(end_time[9:])).total_seconds() transcript_segments.append((start_seconds, end_seconds, text)) return transcript_segments for data like [00:00:14.240 --> 00:00:14.420] the [00:00:14.420 --> 00:00:14.860] robust [00:00:14.860 --> 00:00:15.020] ness [00:00:15.020 --> 00:00:15.140] of [00:00:15.140 --> 00:00:15.500] neural [00:00:15.500 --> 00:00:15.870] networks [00:00:15.870 --> 00:00:16.200] . [00:00:16.200 --> 00:00:16.410] And [00:00:16.410 --> 00:00:16.700] this [00:00:16.700 --> 00:00:16.840] is [00:00:16.840 --> 00:00:17.200] joint write a merge() function that (1) calls parse and (2) merges words into sentences that end in period. Start with the first word and end with the period. Return a list of strings.

Output

import re from datetime import timedelta def parse_transcript(content): transcript_segments = [] pattern = r'\[(\d{2}:\d{2}:\d{2}\.\d{3}) --> (\d{2}:\d{2}:\d{2}\.\d{3})\] (.*)' matches = re.findall(pattern, content) for start_time, end_time, text in matches: start_seconds = timedelta(hours=int(start_time[:2]), minutes=int(start_time[3:5]), seconds=int(start_time[6:8]), milliseconds=int(start_time[9:])).total_seconds() end_seconds = timedelta(hours=int(end_time[:2]), minutes=int(end_time[3:5]), seconds=int(end_time[6:8]), milliseconds=int(end_time[9:])).total_seconds() transcript_segments.append((start_seconds, end_seconds, text)) return transcript_segments def merge(content): transcript_segments = parse_transcript(content) sentences = [] current_sentence = "" for segment in transcript_segments: text = segment[2] current_sentence += text.strip() + " " if text.strip().endswith("."): sentences.append(current_sentence.strip()) current_sentence = "" return sentences # Example usage data = """ [00:00:14.240 --> 00:00:14.420] the [00:00:14.420 --> 00:00:14.860] robust [00:00:14.860 --> 00:00:15.020] ness [00:00:15.020 --> 00:00:15.140] of [00:00:15.140 --> 00:00:15.500] neural [00:00:15.500 --> 00:00:15.870] networks [00:00:15.870 --> 00:00:16.200] . [00:00:16.200 --> 00:00:16.410] And [00:00:16.410 --> 00:00:16.700] this [00:00:16.700 --> 00:00:16.840] is [00:00:16.840 --> 00:00:17.200] joint """ result = merge(data) print(result)

Extract Code

I extracted the following code from that output: 

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import re
from datetime import timedelta

def parse_transcript(content):
    transcript_segments = []
    pattern = r'\[(\d{2}:\d{2}:\d{2}\.\d{3}) --> (\d{2}:\d{2}:\d{2}\.\d{3})\]  (.*)'
    matches = re.findall(pattern, content)

    for start_time, end_time, text in matches:
        start_seconds = timedelta(hours=int(start_time[:2]), minutes=int(start_time[3:5]), seconds=int(start_time[6:8]), milliseconds=int(start_time[9:])).total_seconds()
        end_seconds = timedelta(hours=int(end_time[:2]), minutes=int(end_time[3:5]), seconds=int(end_time[6:8]), milliseconds=int(end_time[9:])).total_seconds()
        transcript_segments.append((start_seconds, end_seconds, text))

    return transcript_segments

def merge(content):
    transcript_segments = parse_transcript(content)
    sentences = []
    current_sentence = ""

    for segment in transcript_segments:
        text = segment[2]
        current_sentence += text.strip() + " "
        if text.strip().endswith("."):
            sentences.append(current_sentence.strip())
            current_sentence = ""

    return sentences

Run Code Interpreter

Running the following program: 

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import re
from datetime import timedelta

def parse_transcript(content):
    transcript_segments = []
    pattern = r'\[(\d{2}:\d{2}:\d{2}\.\d{3}) --> (\d{2}:\d{2}:\d{2}\.\d{3})\]  (.*)'
    matches = re.findall(pattern, content)

    for start_time, end_time, text in matches:
        start_seconds = timedelta(hours=int(start_time[:2]), minutes=int(start_time[3:5]), seconds=int(start_time[6:8]), milliseconds=int(start_time[9:])).total_seconds()
        end_seconds = timedelta(hours=int(end_time[:2]), minutes=int(end_time[3:5]), seconds=int(end_time[6:8]), milliseconds=int(end_time[9:])).total_seconds()
        transcript_segments.append((start_seconds, end_seconds, text))

    return transcript_segments

def merge(content):
    transcript_segments = parse_transcript(content)
    sentences = []
    current_sentence = ""

    for segment in transcript_segments:
        text = segment[2]
        current_sentence += text.strip() + " "
        if text.strip().endswith("."):
            sentences.append(current_sentence.strip())
            current_sentence = ""

    return sentences



def parse_transcript(content):
    transcript_segments = []
    pattern = r'\[(\d{2}:\d{2}:\d{2}\.\d{3}) --> (\d{2}:\d{2}:\d{2}\.\d{3})\]  (.*)'
    matches = re.findall(pattern, content)

    for start_time, end_time, text in matches:
        start_seconds = timedelta(hours=int(start_time[:2]), minutes=int(start_time[3:5]), seconds=int(start_time[6:8]), milliseconds=int(start_time[9:])).total_seconds()
        end_seconds = timedelta(hours=int(end_time[:2]), minutes=int(end_time[3:5]), seconds=int(end_time[6:8]), milliseconds=int(end_time[9:])).total_seconds()
        transcript_segments.append((start_seconds, end_seconds, text))

    return transcript_segments


answer = merge("[00:00:14.240 --> 00:00:14.420]   the\n[00:00:14.420 --> 00:00:14.860]   robust\n[00:00:14.860 --> 00:00:15.020]  ness\n[00:00:15.020 --> 00:00:15.140]   of\n[00:00:15.140 --> 00:00:15.500]   neural\n[00:00:15.500 --> 00:00:15.870]   networks\n[00:00:15.870 --> 00:00:16.200]  .\n[00:00:16.200 --> 00:00:16.410]   And\n[00:00:16.410 --> 00:00:16.700]   this\n[00:00:16.700 --> 00:00:16.840]   is\n[00:00:16.840 --> 00:00:17.200]   joint\n")
expected = [' the robustness of neural networks.', ' And this is joint']
assert answer == expected, f'Wrong answer; got {answer} instead of {expected}'
print('All tests passed')
And got the output: Traceback (most recent call last): File "/usr/src/app/main.py", line 47, in <module> assert answer == expected, f'Wrong answer; got {answer} instead of {expected}' ^^^^^^^^^^^^^^^^^^ AssertionError: Wrong answer; got ['the robust ness of neural networks .'] instead of [' the robustness of neural networks.', ' And this is joint']

Substring Evaluation

Testing if the previous output contains the string All tests passed: False

Initial Query

Given a parse function like def parse_transcript(content): transcript_segments = [] pattern = r'\[(\d{2}:\d{2}:\d{2}\.\d{3}) --> (\d{2}:\d{2}:\d{2}\.\d{3})\] (.*)' matches = re.findall(pattern, content) for start_time, end_time, text in matches: start_seconds = timedelta(hours=int(start_time[:2]), minutes=int(start_time[3:5]), seconds=int(start_time[6:8]), milliseconds=int(start_time[9:])).total_seconds() end_seconds = timedelta(hours=int(end_time[:2]), minutes=int(end_time[3:5]), seconds=int(end_time[6:8]), milliseconds=int(end_time[9:])).total_seconds() transcript_segments.append((start_seconds, end_seconds, text)) return transcript_segments for data like [00:00:14.240 --> 00:00:14.420] the [00:00:14.420 --> 00:00:14.860] robust [00:00:14.860 --> 00:00:15.020] ness [00:00:15.020 --> 00:00:15.140] of [00:00:15.140 --> 00:00:15.500] neural [00:00:15.500 --> 00:00:15.870] networks [00:00:15.870 --> 00:00:16.200] . [00:00:16.200 --> 00:00:16.410] And [00:00:16.410 --> 00:00:16.700] this [00:00:16.700 --> 00:00:16.840] is [00:00:16.840 --> 00:00:17.200] joint write a merge() function that (1) calls parse and (2) merges words into sentences that end in period. Start with the first word and end with the period. Return a list of strings.

LLM Generation

Query

Given a parse function like def parse_transcript(content): transcript_segments = [] pattern = r'\[(\d{2}:\d{2}:\d{2}\.\d{3}) --> (\d{2}:\d{2}:\d{2}\.\d{3})\] (.*)' matches = re.findall(pattern, content) for start_time, end_time, text in matches: start_seconds = timedelta(hours=int(start_time[:2]), minutes=int(start_time[3:5]), seconds=int(start_time[6:8]), milliseconds=int(start_time[9:])).total_seconds() end_seconds = timedelta(hours=int(end_time[:2]), minutes=int(end_time[3:5]), seconds=int(end_time[6:8]), milliseconds=int(end_time[9:])).total_seconds() transcript_segments.append((start_seconds, end_seconds, text)) return transcript_segments for data like [00:00:14.240 --> 00:00:14.420] the [00:00:14.420 --> 00:00:14.860] robust [00:00:14.860 --> 00:00:15.020] ness [00:00:15.020 --> 00:00:15.140] of [00:00:15.140 --> 00:00:15.500] neural [00:00:15.500 --> 00:00:15.870] networks [00:00:15.870 --> 00:00:16.200] . [00:00:16.200 --> 00:00:16.410] And [00:00:16.410 --> 00:00:16.700] this [00:00:16.700 --> 00:00:16.840] is [00:00:16.840 --> 00:00:17.200] joint write a merge() function that (1) calls parse and (2) merges words into sentences that end in period. Start with the first word and end with the period. Return a list of strings.

Output

Here's a possible implementation of the merge function: 

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import re
from datetime import timedelta

def parse_transcript(content):
    transcript_segments = []
    pattern = r'\[(\d{2}:\d{2}:\d{2}\.\d{3}) --> (\d{2}:\d{2}:\d{2}\.\d{3})\]  (.*)'
    matches = re.findall(pattern, content)

    for start_time, end_time, text in matches:
        start_seconds = timedelta(hours=int(start_time[:2]), minutes=int(start_time[3:5]), seconds=int(start_time[6:8]), milliseconds=int(start_time[9:])).total_seconds()
        end_seconds = timedelta(hours=int(end_time[:2]), minutes=int(end_time[3:5]), seconds=int(end_time[6:8]), milliseconds=int(end_time[9:])).total_seconds()
        transcript_segments.append((start_seconds, end_seconds, text))

    return transcript_segments

def merge(content):
    transcript_segments = parse_transcript(content)
    sentences = []
    current_sentence = ""

    for segment in transcript_segments:
        text = segment[2]
        
        if text.endswith('.'):
            current_sentence += text
            sentences.append(current_sentence)
            current_sentence = ""
        else:
            current_sentence += text + " "

    if current_sentence:
        sentences.append(current_sentence)

    return sentences

# Example usage
content = """
[00:00:14.240 --> 00:00:14.420]   the
[00:00:14.420 --> 00:00:14.860]   robust
[00:00:14.860 --> 00:00:15.020]  ness
[00:00:15.020 --> 00:00:15.140]   of
[00:00:15.140 --> 00:00:15.500]   neural
[00:00:15.500 --> 00:00:15.870]   networks
[00:00:15.870 --> 00:00:16.200]  .
[00:00:16.200 --> 00:00:16.410]   And
[00:00:16.410 --> 00:00:16.700]   this
[00:00:16.700 --> 00:00:16.840]   is
[00:00:16.840 --> 00:00:17.200]   joint
"""

result = merge(content)
for sentence in result:
    print(sentence.strip())
This merge function will parse the input content, merge words into sentences that end in a period, and return a list of strings representing the sentences.

Extract Code

I extracted the following code from that output: 

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import re
from datetime import timedelta

def parse_transcript(content):
    transcript_segments = []
    pattern = r'\[(\d{2}:\d{2}:\d{2}\.\d{3}) --> (\d{2}:\d{2}:\d{2}\.\d{3})\]  (.*)'
    matches = re.findall(pattern, content)

    for start_time, end_time, text in matches:
        start_seconds = timedelta(hours=int(start_time[:2]), minutes=int(start_time[3:5]), seconds=int(start_time[6:8]), milliseconds=int(start_time[9:])).total_seconds()
        end_seconds = timedelta(hours=int(end_time[:2]), minutes=int(end_time[3:5]), seconds=int(end_time[6:8]), milliseconds=int(end_time[9:])).total_seconds()
        transcript_segments.append((start_seconds, end_seconds, text))

    return transcript_segments

def merge(content):
    transcript_segments = parse_transcript(content)
    sentences = []
    current_sentence = ""

    for segment in transcript_segments:
        text = segment[2]
        
        if text.endswith('.'):
            current_sentence += text
            sentences.append(current_sentence)
            current_sentence = ""
        else:
            current_sentence += text + " "

    if current_sentence:
        sentences.append(current_sentence)

    return sentences

# Example usage
content = """
[00:00:14.240 --> 00:00:14.420]   the
[00:00:14.420 --> 00:00:14.860]   robust
[00:00:14.860 --> 00:00:15.020]  ness
[00:00:15.020 --> 00:00:15.140]   of
[00:00:15.140 --> 00:00:15.500]   neural
[00:00:15.500 --> 00:00:15.870]   networks
[00:00:15.870 --> 00:00:16.200]  .
[00:00:16.200 --> 00:00:16.410]   And
[00:00:16.410 --> 00:00:16.700]   this
[00:00:16.700 --> 00:00:16.840]   is
[00:00:16.840 --> 00:00:17.200]   joint
"""

result = merge(content)
for sentence in result:
    print(sentence.strip())

Run Code Interpreter

Running the following program: 

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import re
from datetime import timedelta

def parse_transcript(content):
    transcript_segments = []
    pattern = r'\[(\d{2}:\d{2}:\d{2}\.\d{3}) --> (\d{2}:\d{2}:\d{2}\.\d{3})\]  (.*)'
    matches = re.findall(pattern, content)

    for start_time, end_time, text in matches:
        start_seconds = timedelta(hours=int(start_time[:2]), minutes=int(start_time[3:5]), seconds=int(start_time[6:8]), milliseconds=int(start_time[9:])).total_seconds()
        end_seconds = timedelta(hours=int(end_time[:2]), minutes=int(end_time[3:5]), seconds=int(end_time[6:8]), milliseconds=int(end_time[9:])).total_seconds()
        transcript_segments.append((start_seconds, end_seconds, text))

    return transcript_segments

def merge(content):
    transcript_segments = parse_transcript(content)
    sentences = []
    current_sentence = ""

    for segment in transcript_segments:
        text = segment[2]
        
        if text.endswith('.'):
            current_sentence += text
            sentences.append(current_sentence)
            current_sentence = ""
        else:
            current_sentence += text + " "

    if current_sentence:
        sentences.append(current_sentence)

    return sentences

# Example usage
content = """
[00:00:14.240 --> 00:00:14.420]   the
[00:00:14.420 --> 00:00:14.860]   robust
[00:00:14.860 --> 00:00:15.020]  ness
[00:00:15.020 --> 00:00:15.140]   of
[00:00:15.140 --> 00:00:15.500]   neural
[00:00:15.500 --> 00:00:15.870]   networks
[00:00:15.870 --> 00:00:16.200]  .
[00:00:16.200 --> 00:00:16.410]   And
[00:00:16.410 --> 00:00:16.700]   this
[00:00:16.700 --> 00:00:16.840]   is
[00:00:16.840 --> 00:00:17.200]   joint
"""

result = merge(content)
for sentence in result:
    print(sentence.strip())




def parse_transcript(content):
    transcript_segments = []
    pattern = r'\[(\d{2}:\d{2}:\d{2}\.\d{3}) --> (\d{2}:\d{2}:\d{2}\.\d{3})\]  (.*)'
    matches = re.findall(pattern, content)

    for start_time, end_time, text in matches:
        start_seconds = timedelta(hours=int(start_time[:2]), minutes=int(start_time[3:5]), seconds=int(start_time[6:8]), milliseconds=int(start_time[9:])).total_seconds()
        end_seconds = timedelta(hours=int(end_time[:2]), minutes=int(end_time[3:5]), seconds=int(end_time[6:8]), milliseconds=int(end_time[9:])).total_seconds()
        transcript_segments.append((start_seconds, end_seconds, text))

    return transcript_segments


answer = merge("[00:00:14.240 --> 00:00:14.420]   the\n[00:00:14.420 --> 00:00:14.860]   robust\n[00:00:14.860 --> 00:00:15.020]  ness\n[00:00:15.020 --> 00:00:15.140]   of\n[00:00:15.140 --> 00:00:15.500]   neural\n[00:00:15.500 --> 00:00:15.870]   networks\n[00:00:15.870 --> 00:00:16.200]  .\n[00:00:16.200 --> 00:00:16.410]   And\n[00:00:16.410 --> 00:00:16.700]   this\n[00:00:16.700 --> 00:00:16.840]   is\n[00:00:16.840 --> 00:00:17.200]   joint\n")
expected = [' the robustness of neural networks.', ' And this is joint']
assert answer == expected, f'Wrong answer; got {answer} instead of {expected}'
print('All tests passed')
And got the output: the robust ness of neural networks . And this is joint Traceback (most recent call last): File "/usr/src/app/main.py", line 74, in <module> assert answer == expected, f'Wrong answer; got {answer} instead of {expected}' ^^^^^^^^^^^^^^^^^^ AssertionError: Wrong answer; got [' the robust ness of neural networks .', ' And this is joint '] instead of [' the robustness of neural networks.', ' And this is joint']

Substring Evaluation

Testing if the previous output contains the string All tests passed: False