debgpt v0.4.90 has been uploaded to NEW, targeting at unstable.
This tool is still under development, new features will be added later.
Usage examples can be found in debgpt(1) or README.md .
They are the same file.
During my (limited number) of experiments when developing this tool,
LLMs are good at:
1. $ debgpt git commit
(many recent git commits in debgpt repo are generated using LLM)
This is the one I like most so far. This will likely become a part of
my git workflow.
2. summarizing arbitrary texts in pretty format
3. explaining arbitrary code files
4. fortune, e.g. $ debgpt fortune :joke
5. writing boring boiler plate code (such as matplotlib)
LLMs are bad at:
1. logic and deduction
for example, it does not always tell the relation between
"SyntaxError: print 'hello world'" and an upstream PR named "initial
python3 support.
(Maybe chain of thoguht can improve this but I postponed it)
2. generating unix-format patches
Let it give you the edited files directly, instead of the diff.
This tool is not specific to Debian distribution. Adding additional text
sources like Arch Wiki, Gentoo Policy/Wiki is very easy and planned
as future feature. Or you can load these web pages through
`debgpt --cmd 'curl <archwiki.html>'`.
Support for dealing very long documents will be further investigated
in future releases.
On 1/3/24 20:07, Mo Zhou wrote:
I have implemented the OpenAI API frontend, with streaming to terminal
enabled.
On 1/2/24 17:07, M. Zhou wrote:
Following what has been discussed in d-project in an offtopic
subthread, I prepared some demo on imagined use cases to
leverage LLMs to help debian development.
https://salsa.debian.org/deeplearning-team/debgpt
