Initial Query
Why isn't this working
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16 | @app.route('/getsimilar', methods=['GET'])
def getsimilar():
print('args',request.args)
positive = request.args.get('positive', '')
positive = positive.split("##")
negative = request.args.get('negative', '')
negative = negative.split("##")
keep_yes = [i for i,x in enumerate(titles) if x in positive]
set1_yes = emb[keep_yes]
keep_no = [i for i,x in enumerate(titles) if x in negative]
set1_no = emb[keep_no]
print("OK", len(set1_yes), len(set1_no))
|
I see
| args ImmutableMultiDict([('positive', 'Title: Towards Evaluating the Robustness of Neural Networks
Authors: Nicholas Carlini; David Wagner'), ('negative', 'Title: On Evaluating Adversarial Robustness Authors: Nicholas Carlini; Anish Athalye; Nicolas Papernot; Wieland Brendel; Jonas Rauber; Dimitris Tsipras; Ian Goodfellow; Aleksander Madry; Alexey Kurakin}')])
OK 1 0
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Why don't I see OK 1 1? Instead it just says OK 1 0. List exactly one reason explaining what's wrong and what one change would fix it.
LLM Generation
Query
Why isn't this working
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16 | @app.route('/getsimilar', methods=['GET'])
def getsimilar():
print('args',request.args)
positive = request.args.get('positive', '')
positive = positive.split("##")
negative = request.args.get('negative', '')
negative = negative.split("##")
keep_yes = [i for i,x in enumerate(titles) if x in positive]
set1_yes = emb[keep_yes]
keep_no = [i for i,x in enumerate(titles) if x in negative]
set1_no = emb[keep_no]
print("OK", len(set1_yes), len(set1_no))
|
I see
| args ImmutableMultiDict([('positive', 'Title: Towards Evaluating the Robustness of Neural Networks
Authors: Nicholas Carlini; David Wagner'), ('negative', 'Title: On Evaluating Adversarial Robustness Authors: Nicholas Carlini; Anish Athalye; Nicolas Papernot; Wieland Brendel; Jonas Rauber; Dimitris Tsipras; Ian Goodfellow; Aleksander Madry; Alexey Kurakin}')])
OK 1 0
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Why don't I see OK 1 1? Instead it just says OK 1 0. List exactly one reason explaining what's wrong and what one change would fix it.
Output
The problem is an exact string match failure between the `titles` list and the strings provided in the `negative` argument. Notice the subtle difference in spacing/formatting: the `negative` string from the request has "On Evaluating Adversarial Robustness" while the `titles` list (not shown in the provided code, but inferable) likely has something like "On Evaluating Adversarial Robustness" or "On Evaluating Adversarial Robustness ". The extra space or missing space is causing the `x in negative` check within the list comprehension to fail.
**The Fix:** Normalize the strings before comparison by stripping leading/trailing whitespace and potentially collapsing multiple spaces into single spaces.
Change this line:
| keep_no = [i for i,x in enumerate(titles) if x in negative]
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To this:
| import re
keep_no = [i for i, x in enumerate(titles) if any(re.sub(r'\s+', ' ', x.strip()) == re.sub(r'\s+', ' ', neg.strip()) for neg in negative)]
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This code first uses `strip()` to remove leading/trailing whitespace from both the title (`x`) and each negative example (`neg`). Then it uses `re.sub(r'\s+', ' ', ...)` to replace multiple spaces with a single space, ensuring consistent spacing. Finally, it uses `any()` to check if the normalized title matches any of the normalized negative examples. This addresses potential discrepancies in whitespace and ensures a more robust comparison.
LLM Generation
Query
I asked a question about why some code was incorrect. The answer is "because the input contains an extra curly brace }". Does this student answer say that?
The problem is an exact string match failure between the `titles` list and the strings provided in the `negative` argument. Notice the subtle difference in spacing/formatting: the `negative` string from the request has "On Evaluating Adversarial Robustness" while the `titles` list (not shown in the provided code, but inferable) likely has something like "On Evaluating Adversarial Robustness" or "On Evaluating Adversarial Robustness ". The extra space or missing space is causing the `x in negative` check within the list comprehension to fail.
**The Fix:** Normalize the strings before comparison by stripping leading/trailing whitespace and potentially collapsing multiple spaces into single spaces.
Change this line:
| keep_no = [i for i,x in enumerate(titles) if x in negative]
|
To this:
| import re
keep_no = [i for i, x in enumerate(titles) if any(re.sub(r'\s+', ' ', x.strip()) == re.sub(r'\s+', ' ', neg.strip()) for neg in negative)]
|
This code first uses `strip()` to remove leading/trailing whitespace from both the title (`x`) and each negative example (`neg`). Then it uses `re.sub(r'\s+', ' ', ...)` to replace multiple spaces with a single space, ensuring consistent spacing. Finally, it uses `any()` to check if the normalized title matches any of the normalized negative examples. This addresses potential discrepancies in whitespace and ensures a more robust comparison.
Answer either 'The student passes' or 'The student fails'.
Output
The student fails.
Substring Evaluation
Testing if the previous output contains the string student passes: False
Initial Query
Why isn't this working
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16 | @app.route('/getsimilar', methods=['GET'])
def getsimilar():
print('args',request.args)
positive = request.args.get('positive', '')
positive = positive.split("##")
negative = request.args.get('negative', '')
negative = negative.split("##")
keep_yes = [i for i,x in enumerate(titles) if x in positive]
set1_yes = emb[keep_yes]
keep_no = [i for i,x in enumerate(titles) if x in negative]
set1_no = emb[keep_no]
print("OK", len(set1_yes), len(set1_no))
|
I see
| args ImmutableMultiDict([('positive', 'Title: Towards Evaluating the Robustness of Neural Networks
Authors: Nicholas Carlini; David Wagner'), ('negative', 'Title: On Evaluating Adversarial Robustness Authors: Nicholas Carlini; Anish Athalye; Nicolas Papernot; Wieland Brendel; Jonas Rauber; Dimitris Tsipras; Ian Goodfellow; Aleksander Madry; Alexey Kurakin}')])
OK 1 0
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Why don't I see OK 1 1? Instead it just says OK 1 0. List exactly one reason explaining what's wrong and what one change would fix it.
LLM Generation
Query
Why isn't this working
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16 | @app.route('/getsimilar', methods=['GET'])
def getsimilar():
print('args',request.args)
positive = request.args.get('positive', '')
positive = positive.split("##")
negative = request.args.get('negative', '')
negative = negative.split("##")
keep_yes = [i for i,x in enumerate(titles) if x in positive]
set1_yes = emb[keep_yes]
keep_no = [i for i,x in enumerate(titles) if x in negative]
set1_no = emb[keep_no]
print("OK", len(set1_yes), len(set1_no))
|
I see
| args ImmutableMultiDict([('positive', 'Title: Towards Evaluating the Robustness of Neural Networks
Authors: Nicholas Carlini; David Wagner'), ('negative', 'Title: On Evaluating Adversarial Robustness Authors: Nicholas Carlini; Anish Athalye; Nicolas Papernot; Wieland Brendel; Jonas Rauber; Dimitris Tsipras; Ian Goodfellow; Aleksander Madry; Alexey Kurakin}')])
OK 1 0
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Why don't I see OK 1 1? Instead it just says OK 1 0. List exactly one reason explaining what's wrong and what one change would fix it.
Output
The issue is an exact string matching problem between the `titles` list and the strings provided in the `negative` argument. The strings don't match exactly due to differences in whitespace (likely extra spaces or different types of whitespace characters).
**The Fix:** Use a more flexible comparison method that accounts for potential whitespace variations. Replace the exact string comparison with a whitespace-insensitive comparison.
Change this line:
| keep_no = [i for i,x in enumerate(titles) if x in negative]
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to:
| keep_no = [i for i, x in enumerate(titles) if any(y.strip() == x.strip() for y in negative)]
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This change uses `.strip()` to remove leading/trailing whitespace from both the titles and the provided negative examples before comparing them. The `any()` function checks if *any* of the stripped negative strings match the stripped title, handling cases where multiple negative examples are provided. This approach ensures a match even if there are minor whitespace discrepancies.
LLM Generation
Query
I asked a question about why some code was incorrect. The answer is "because the input contains an extra curly brace }". Does this student answer say that?
The issue is an exact string matching problem between the `titles` list and the strings provided in the `negative` argument. The strings don't match exactly due to differences in whitespace (likely extra spaces or different types of whitespace characters).
**The Fix:** Use a more flexible comparison method that accounts for potential whitespace variations. Replace the exact string comparison with a whitespace-insensitive comparison.
Change this line:
| keep_no = [i for i,x in enumerate(titles) if x in negative]
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to:
| keep_no = [i for i, x in enumerate(titles) if any(y.strip() == x.strip() for y in negative)]
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This change uses `.strip()` to remove leading/trailing whitespace from both the titles and the provided negative examples before comparing them. The `any()` function checks if *any* of the stripped negative strings match the stripped title, handling cases where multiple negative examples are provided. This approach ensures a match even if there are minor whitespace discrepancies.
Answer either 'The student passes' or 'The student fails'.
Output
The student fails.
Substring Evaluation
Testing if the previous output contains the string student passes: False
Initial Query
Why isn't this working
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16 | @app.route('/getsimilar', methods=['GET'])
def getsimilar():
print('args',request.args)
positive = request.args.get('positive', '')
positive = positive.split("##")
negative = request.args.get('negative', '')
negative = negative.split("##")
keep_yes = [i for i,x in enumerate(titles) if x in positive]
set1_yes = emb[keep_yes]
keep_no = [i for i,x in enumerate(titles) if x in negative]
set1_no = emb[keep_no]
print("OK", len(set1_yes), len(set1_no))
|
I see
| args ImmutableMultiDict([('positive', 'Title: Towards Evaluating the Robustness of Neural Networks
Authors: Nicholas Carlini; David Wagner'), ('negative', 'Title: On Evaluating Adversarial Robustness Authors: Nicholas Carlini; Anish Athalye; Nicolas Papernot; Wieland Brendel; Jonas Rauber; Dimitris Tsipras; Ian Goodfellow; Aleksander Madry; Alexey Kurakin}')])
OK 1 0
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Why don't I see OK 1 1? Instead it just says OK 1 0. List exactly one reason explaining what's wrong and what one change would fix it.
LLM Generation
Query
Why isn't this working
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16 | @app.route('/getsimilar', methods=['GET'])
def getsimilar():
print('args',request.args)
positive = request.args.get('positive', '')
positive = positive.split("##")
negative = request.args.get('negative', '')
negative = negative.split("##")
keep_yes = [i for i,x in enumerate(titles) if x in positive]
set1_yes = emb[keep_yes]
keep_no = [i for i,x in enumerate(titles) if x in negative]
set1_no = emb[keep_no]
print("OK", len(set1_yes), len(set1_no))
|
I see
| args ImmutableMultiDict([('positive', 'Title: Towards Evaluating the Robustness of Neural Networks
Authors: Nicholas Carlini; David Wagner'), ('negative', 'Title: On Evaluating Adversarial Robustness Authors: Nicholas Carlini; Anish Athalye; Nicolas Papernot; Wieland Brendel; Jonas Rauber; Dimitris Tsipras; Ian Goodfellow; Aleksander Madry; Alexey Kurakin}')])
OK 1 0
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Why don't I see OK 1 1? Instead it just says OK 1 0. List exactly one reason explaining what's wrong and what one change would fix it.
Output
The problem is that the titles in the `titles` list and the titles provided in the request arguments don't match exactly. Likely, there are extra spaces or slight differences in capitalization or punctuation.
**The fix:** Preprocess both the `titles` list and the incoming title strings to ensure consistency. Specifically, strip leading/trailing whitespace and convert both to lowercase before comparison.
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21 | @app.route('/getsimilar', methods=['GET'])
def getsimilar():
print('args',request.args)
positive = request.args.get('positive', '')
positive = positive.split("##")
positive = [s.strip().lower() for s in positive] # <--- Add this line
negative = request.args.get('negative', '')
negative = negative.split("##")
negative = [s.strip().lower() for s in negative] # <--- Add this line
titles_lower = [t.strip().lower() for t in titles] # <--- Add this line
keep_yes = [i for i,x in enumerate(titles_lower) if x in positive] # Use titles_lower
set1_yes = emb[keep_yes]
keep_no = [i for i,x in enumerate(titles_lower) if x in negative] # Use titles_lower
set1_no = emb[keep_no]
print("OK", len(set1_yes), len(set1_no))
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This ensures that minor formatting differences don't prevent matches.
LLM Generation
Query
I asked a question about why some code was incorrect. The answer is "because the input contains an extra curly brace }". Does this student answer say that?
The problem is that the titles in the `titles` list and the titles provided in the request arguments don't match exactly. Likely, there are extra spaces or slight differences in capitalization or punctuation.
**The fix:** Preprocess both the `titles` list and the incoming title strings to ensure consistency. Specifically, strip leading/trailing whitespace and convert both to lowercase before comparison.
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21 | @app.route('/getsimilar', methods=['GET'])
def getsimilar():
print('args',request.args)
positive = request.args.get('positive', '')
positive = positive.split("##")
positive = [s.strip().lower() for s in positive] # <--- Add this line
negative = request.args.get('negative', '')
negative = negative.split("##")
negative = [s.strip().lower() for s in negative] # <--- Add this line
titles_lower = [t.strip().lower() for t in titles] # <--- Add this line
keep_yes = [i for i,x in enumerate(titles_lower) if x in positive] # Use titles_lower
set1_yes = emb[keep_yes]
keep_no = [i for i,x in enumerate(titles_lower) if x in negative] # Use titles_lower
set1_no = emb[keep_no]
print("OK", len(set1_yes), len(set1_no))
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This ensures that minor formatting differences don't prevent matches.
Answer either 'The student passes' or 'The student fails'.
Output
The student fails.
Substring Evaluation
Testing if the previous output contains the string student passes: False
Initial Query
Why isn't this working
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16 | @app.route('/getsimilar', methods=['GET'])
def getsimilar():
print('args',request.args)
positive = request.args.get('positive', '')
positive = positive.split("##")
negative = request.args.get('negative', '')
negative = negative.split("##")
keep_yes = [i for i,x in enumerate(titles) if x in positive]
set1_yes = emb[keep_yes]
keep_no = [i for i,x in enumerate(titles) if x in negative]
set1_no = emb[keep_no]
print("OK", len(set1_yes), len(set1_no))
|
I see
| args ImmutableMultiDict([('positive', 'Title: Towards Evaluating the Robustness of Neural Networks
Authors: Nicholas Carlini; David Wagner'), ('negative', 'Title: On Evaluating Adversarial Robustness Authors: Nicholas Carlini; Anish Athalye; Nicolas Papernot; Wieland Brendel; Jonas Rauber; Dimitris Tsipras; Ian Goodfellow; Aleksander Madry; Alexey Kurakin}')])
OK 1 0
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Why don't I see OK 1 1? Instead it just says OK 1 0. List exactly one reason explaining what's wrong and what one change would fix it.
LLM Generation
Query
Why isn't this working
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16 | @app.route('/getsimilar', methods=['GET'])
def getsimilar():
print('args',request.args)
positive = request.args.get('positive', '')
positive = positive.split("##")
negative = request.args.get('negative', '')
negative = negative.split("##")
keep_yes = [i for i,x in enumerate(titles) if x in positive]
set1_yes = emb[keep_yes]
keep_no = [i for i,x in enumerate(titles) if x in negative]
set1_no = emb[keep_no]
print("OK", len(set1_yes), len(set1_no))
|
I see
| args ImmutableMultiDict([('positive', 'Title: Towards Evaluating the Robustness of Neural Networks
Authors: Nicholas Carlini; David Wagner'), ('negative', 'Title: On Evaluating Adversarial Robustness Authors: Nicholas Carlini; Anish Athalye; Nicolas Papernot; Wieland Brendel; Jonas Rauber; Dimitris Tsipras; Ian Goodfellow; Aleksander Madry; Alexey Kurakin}')])
OK 1 0
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Why don't I see OK 1 1? Instead it just says OK 1 0. List exactly one reason explaining what's wrong and what one change would fix it.
Output
The problem is that the titles in your `titles` list don't exactly match the titles provided in the query parameters. Specifically, whitespace differences are likely the culprit. The query string values have extra spaces and newlines.
**The fix:** Normalize the whitespace in both the query parameters and the `titles` list before comparison. This can be achieved by stripping leading/trailing whitespace and replacing internal multiple spaces with single spaces.
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21 | @app.route('/getsimilar', methods=['GET'])
def getsimilar():
print('args',request.args)
positive = request.args.get('positive', '')
positive = positive.split("##")
positive = [p.replace('\n', ' ').strip() for p in positive] # normalize whitespace
positive = [' '.join(p.split()) for p in positive] # normalize whitespace
negative = request.args.get('negative', '')
negative = negative.split("##")
negative = [n.replace('\n', ' ').strip() for n in negative] # normalize whitespace
negative = [' '.join(n.split()) for n in negative] # normalize whitespace
keep_yes = [i for i,x in enumerate(titles) if x in positive]
set1_yes = emb[keep_yes]
keep_no = [i for i,x in enumerate(titles) if x in negative]
set1_no = emb[keep_no]
print("OK", len(set1_yes), len(set1_no))
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You should also apply the same whitespace normalization to your `titles` list when you initially create it. This ensures consistency throughout your application.
| titles = [...] # wherever you define titles
titles = [t.replace('\n', ' ').strip() for t in titles] # normalize whitespace
titles = [' '.join(t.split()) for t in titles] # normalize whitespace
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LLM Generation
Query
I asked a question about why some code was incorrect. The answer is "because the input contains an extra curly brace }". Does this student answer say that?
The problem is that the titles in your `titles` list don't exactly match the titles provided in the query parameters. Specifically, whitespace differences are likely the culprit. The query string values have extra spaces and newlines.
**The fix:** Normalize the whitespace in both the query parameters and the `titles` list before comparison. This can be achieved by stripping leading/trailing whitespace and replacing internal multiple spaces with single spaces.
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21 | @app.route('/getsimilar', methods=['GET'])
def getsimilar():
print('args',request.args)
positive = request.args.get('positive', '')
positive = positive.split("##")
positive = [p.replace('\n', ' ').strip() for p in positive] # normalize whitespace
positive = [' '.join(p.split()) for p in positive] # normalize whitespace
negative = request.args.get('negative', '')
negative = negative.split("##")
negative = [n.replace('\n', ' ').strip() for n in negative] # normalize whitespace
negative = [' '.join(n.split()) for n in negative] # normalize whitespace
keep_yes = [i for i,x in enumerate(titles) if x in positive]
set1_yes = emb[keep_yes]
keep_no = [i for i,x in enumerate(titles) if x in negative]
set1_no = emb[keep_no]
print("OK", len(set1_yes), len(set1_no))
|
You should also apply the same whitespace normalization to your `titles` list when you initially create it. This ensures consistency throughout your application.
| titles = [...] # wherever you define titles
titles = [t.replace('\n', ' ').strip() for t in titles] # normalize whitespace
titles = [' '.join(t.split()) for t in titles] # normalize whitespace
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Answer either 'The student passes' or 'The student fails'.
Output
The student fails.
Substring Evaluation
Testing if the previous output contains the string student passes: False
Initial Query
Why isn't this working
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16 | @app.route('/getsimilar', methods=['GET'])
def getsimilar():
print('args',request.args)
positive = request.args.get('positive', '')
positive = positive.split("##")
negative = request.args.get('negative', '')
negative = negative.split("##")
keep_yes = [i for i,x in enumerate(titles) if x in positive]
set1_yes = emb[keep_yes]
keep_no = [i for i,x in enumerate(titles) if x in negative]
set1_no = emb[keep_no]
print("OK", len(set1_yes), len(set1_no))
|
I see
| args ImmutableMultiDict([('positive', 'Title: Towards Evaluating the Robustness of Neural Networks
Authors: Nicholas Carlini; David Wagner'), ('negative', 'Title: On Evaluating Adversarial Robustness Authors: Nicholas Carlini; Anish Athalye; Nicolas Papernot; Wieland Brendel; Jonas Rauber; Dimitris Tsipras; Ian Goodfellow; Aleksander Madry; Alexey Kurakin}')])
OK 1 0
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Why don't I see OK 1 1? Instead it just says OK 1 0. List exactly one reason explaining what's wrong and what one change would fix it.
LLM Generation
Query
Why isn't this working
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16 | @app.route('/getsimilar', methods=['GET'])
def getsimilar():
print('args',request.args)
positive = request.args.get('positive', '')
positive = positive.split("##")
negative = request.args.get('negative', '')
negative = negative.split("##")
keep_yes = [i for i,x in enumerate(titles) if x in positive]
set1_yes = emb[keep_yes]
keep_no = [i for i,x in enumerate(titles) if x in negative]
set1_no = emb[keep_no]
print("OK", len(set1_yes), len(set1_no))
|
I see
| args ImmutableMultiDict([('positive', 'Title: Towards Evaluating the Robustness of Neural Networks
Authors: Nicholas Carlini; David Wagner'), ('negative', 'Title: On Evaluating Adversarial Robustness Authors: Nicholas Carlini; Anish Athalye; Nicolas Papernot; Wieland Brendel; Jonas Rauber; Dimitris Tsipras; Ian Goodfellow; Aleksander Madry; Alexey Kurakin}')])
OK 1 0
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Why don't I see OK 1 1? Instead it just says OK 1 0. List exactly one reason explaining what's wrong and what one change would fix it.
Output
The problem is an exact string matching issue between the `titles` list and the strings provided in the `negative` argument. The strings don't match exactly due to differences in whitespace (likely extra spaces or different types of whitespace characters).
**The Fix:** Use a more robust comparison method that accounts for potential whitespace variations. Replace the exact string comparison with a whitespace-normalized comparison.
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19 | import re
@app.route('/getsimilar', methods=['GET'])
def getsimilar():
print('args',request.args)
positive = request.args.get('positive', '')
positive = positive.split("##")
negative = request.args.get('negative', '')
negative = negative.split("##")
keep_yes = [i for i,x in enumerate(titles) if any(re.sub(r'\s+', ' ', x.lower()) == re.sub(r'\s+', ' ', p.lower()) for p in positive)]
set1_yes = emb[keep_yes]
keep_no = [i for i,x in enumerate(titles) if any(re.sub(r'\s+', ' ', x.lower()) == re.sub(r'\s+', ' ', n.lower()) for n in negative)]
set1_no = emb[keep_no]
print("OK", len(set1_yes), len(set1_no))
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This solution uses `re.sub(r'\s+', ' ', s.lower())` to normalize whitespace by:
1. **Lowercasing:** `.lower()` converts both strings to lowercase to ensure case-insensitive matching.
2. **Whitespace Normalization:** `re.sub(r'\s+', ' ', s)` replaces any sequence of one or more whitespace characters (spaces, tabs, newlines, etc.) with a single space.
This makes the comparison more tolerant to variations in spacing between the input strings and the strings in the `titles` list.
LLM Generation
Query
I asked a question about why some code was incorrect. The answer is "because the input contains an extra curly brace }". Does this student answer say that?
The problem is an exact string matching issue between the `titles` list and the strings provided in the `negative` argument. The strings don't match exactly due to differences in whitespace (likely extra spaces or different types of whitespace characters).
**The Fix:** Use a more robust comparison method that accounts for potential whitespace variations. Replace the exact string comparison with a whitespace-normalized comparison.
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19 | import re
@app.route('/getsimilar', methods=['GET'])
def getsimilar():
print('args',request.args)
positive = request.args.get('positive', '')
positive = positive.split("##")
negative = request.args.get('negative', '')
negative = negative.split("##")
keep_yes = [i for i,x in enumerate(titles) if any(re.sub(r'\s+', ' ', x.lower()) == re.sub(r'\s+', ' ', p.lower()) for p in positive)]
set1_yes = emb[keep_yes]
keep_no = [i for i,x in enumerate(titles) if any(re.sub(r'\s+', ' ', x.lower()) == re.sub(r'\s+', ' ', n.lower()) for n in negative)]
set1_no = emb[keep_no]
print("OK", len(set1_yes), len(set1_no))
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This solution uses `re.sub(r'\s+', ' ', s.lower())` to normalize whitespace by:
1. **Lowercasing:** `.lower()` converts both strings to lowercase to ensure case-insensitive matching.
2. **Whitespace Normalization:** `re.sub(r'\s+', ' ', s)` replaces any sequence of one or more whitespace characters (spaces, tabs, newlines, etc.) with a single space.
This makes the comparison more tolerant to variations in spacing between the input strings and the strings in the `titles` list.
Answer either 'The student passes' or 'The student fails'.
Output
The student fails.
Substring Evaluation
Testing if the previous output contains the string student passes: False