Get output of send command on expect by Ciro Santilli 37 Created 2025-03-20 Updated 2025-07-16
This pattern works well:
set prompt ">>> "
log_user 0
send "What is quantum field theory?\r"
expect -re "(.+)$prompt"
puts -nonewline [join [lrange [lmap line [split $expect_out(1,string) \n] {regsub {\r$} $line ""}] 1 end] "\n"]
Then stdout will contain only the output of the command and nothing else.
You Only Look Once by Ciro Santilli 37 Created 2025-03-20 Updated 2025-07-16
You can get some really sweet pre-trained versions of this, typically trained on the COCO dataset.
AlexNet by Ciro Santilli 37 Created 2025-03-20 Updated 2025-07-16
Became notable for performing extremely well on ImageNet starting in 2012.
It is also notable for being one of the first to make successful use of GPU training rather than GPU training.
Expect HOWTO by Ciro Santilli 37 Created 2025-03-20 Updated 2025-07-16
Expect by Ciro Santilli 37 Created 2025-03-20 Updated 2025-07-16
Value of life by Ciro Santilli 37 Created 2025-03-20 Updated 2025-07-16
Chromium bug by Ciro Santilli 37 Created 2025-03-20 Updated 2025-07-16
HumanEval by Ciro Santilli 37 Created 2025-03-20 Updated 2025-07-16
The tests are present in a gzip inside the Git repo: github.com/openai/human-eval/blob/master/data/HumanEval.jsonl.gz These researchers.
To get a quick overview of the problems with jq:
jq -r '"==== \(.task_id) \(.entry_point)\n\(.prompt)"' <HumanEval.jsonl 
The first two problems are:
==== HumanEval/0 has_close_elements
from typing import List


def has_close_elements(numbers: List[float], threshold: float) -> bool:
    """ Check if in given list of numbers, are any two numbers closer to each other than
    given threshold.
    >>> has_close_elements([1.0, 2.0, 3.0], 0.5)
    False
    >>> has_close_elements([1.0, 2.8, 3.0, 4.0, 5.0, 2.0], 0.3)
    True
    """

==== HumanEval/1 separate_paren_groups
from typing import List


def separate_paren_groups(paren_string: str) -> List[str]:
    """ Input to this function is a string containing multiple groups of nested parentheses. Your goal is to
    separate those group into separate strings and return the list of those.
    Separate groups are balanced (each open brace is properly closed) and not nested within each other
    Ignore any spaces in the input string.
    >>> separate_paren_groups('( ) (( )) (( )( ))')
    ['()', '(())', '(()())']
    """
so we understand that it takes as input an empty function with a docstring and you have to fill the function body.
The paper also shows that there can be other defined functions besides the one you have to implement.
Image segmentation by Ciro Santilli 37 Created 2025-03-20 Updated 2025-07-16
  • OpenAI's GPT-4-turbo can generate and run Python code if it detects that the prompt would be better answered by Python, e.g. maths
This is the fatal flaw of Reddit for aQ&A website. If you are not early on replying to the thread, your comment very quickly disappears due to replies to other comments. This greatly amplifies the fastest gun in the West problem.

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