(Particularly helpful for me since I always have to lookup an old project for “How does one structure ruby test cases with mocha again?” Literally faster to have the LLM boilerplate it than it is to copy/paste and modify.)
LLMS
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Generate test cases automatically with LLM prompt engineering
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You can get arbitrarily creative with it, too: cat script.rb | llm -s ‘This code is janky. Write some test cases for it, focusing particularly on validating the command line args and that it exits prior to calling the API if it detects an error.’ > test/script_test.rb
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Managing LLM Context Windows: Input Truncation Strategy
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"Why did you pipe the output of the git commands to head above?" Because LLMs have limited context windows and if you exceed the length of them this tool fails gracefully, so by habit I chop the input to it down prior to asking to process it.
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LLM CLI Tool Available on GitHub and PyPI
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If you want to play with it, available on pip / Github / etc. Requires an OpenAI account for batteries-included operation or you can install an LLM locally https://
github.com/simonw/llm -
Using LLM CLI for Linux Command Generation and Automation
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You can, of course, imagine many things you could do with this based on whatever you do in the terminal most frequently. A thing I find myself gravitating to immediately is acting as superman: $ llm 'Linux one liner for current date in most commonly used U.S. format please.'
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Using Git diffs with LLM to summarize commit changes
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git show 57ee | head -c 4000 | llm -s 'This is the first part of a diff. What did this commit actually *do*? Your answer should fit in a tweet.'
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Simon Willison’s LLM command line tool demo
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You might not know about @simonw
's command line 'llm' tool. Here let me demo it. git log | head -n 200 | llm -s "Of the most recent 5 commits, which is probably the most important? I use 'Minor' and similar commit messages to mark unimportant commits." -
Flowise: LLM Orchestration Platform Enabling Custom AI Workflows
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Flowise is a horizontal platform, catering different LLM ochestration, models, to enable users craft their own agent/workflow. Although OpenAI is on the lead, but we will soon see more improvement on other LLMs, enabling more possibilities.
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Kaggle Tips for Aspiring Data Scientists
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– Learn somthing while doing it;
– Spending time on Kaggle should make aspiring #datascientists’ knowledge better;
– Stay more organized;
– You don’t have to go for a win;
– Use LLMs: they can help you answer some questions -
Biggest Kaggle Grandmaster Gathering: LLMs and Beyond
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It’s time for our biggest #Kaggle Grandmaster gathering ever!! @ArnoCandel
, @Rob_Mulla
, @ph_singer
, @pa_pfeiffer
, @DmitryLarko
, @Mark_a_Landry
, @_dynamic24_
, @ryan_chesler
, @bmurr26
, Shaikat Galib & @bhutanisanyam1 are now on stage to talk all things #Kaggle, #LLMs & beyond.