sumba101 / githubevaluator

Given a github link to a github user, evaluate all the repos present and select the most complex ones with adequate GPT4 explanation for choice

GithubEvaluator

Given a github username, evaluate all the repositories present and select the most complex ones with adequate GPT4 reports

Metrics to cover

Given a repository, we want to evaluate Complexity, Code Quality, Useful/Impactful-ness, Uniqueness/Toughness a repository is

The following are possible metrics:

• Complexity:
  • Number of languages
  • Amount of bytes per language
  • Number of dependencies*
  • Number of files
  • Number of commits The above metrics can be made into numeric scores each by making use of defined lower and upper thresholds for each metric. The final score can be a weighted sum of all these scores.
• Code Quality:
  • Code Quality from Repository Map
  • Readability of ReadMe Repository Map can be used to create a comprehensive GPT4 report covering naming convention, structure, modularity and understandability. Readability of ReadMe can be evaluated using GPT4 to generate a report on the ReadMe.
• Useful/Impactful-ness:
  • Number of stars
  • Number of forks
  • Number of watchers
  • Number of pull requests
  • Number of issues Like with complexity, we shall set thresholds for each of these and arrive at a score for each of these.
• Uniqueness/Toughness:
  • ReadMe + Description This is a subjective metric and can be arrived at by using GPT4 to generate a report using README and Description to judge difficulty and uniqueness of the implementation .

The goal would be to generate the Uniqueness/Toughness and Code Quality evaluations with GPT4 for the top 5 good repositories ranked using the other metrics.

NOTE *: Number of dependencies function is currently commented out, must test a bit more to ensure generalisability.

How to run

• Clone the repo
• Install the requirements using pip install -r requirements.txt
• Create a file .env and add the following lines

GITHUB_TOKEN='<GITHUB_TOKEN>'
OPENAI_API_KEY='<OPEN_API_KEY>'

To generate a github token, follow the instructions here

To generate an openai api key, follow the instructions here

• Run the script using

python main.py <github_username>

The script will generate a folder ReportCard which will contain the reports for the top 5 repositories. The report will contain the following for each repository:

• Complexity
• Code Quality
• Useful/Impactful-ness

Customization

The prompts used for generating the reports can be found in the file prompts.py. The prompts can be modified to generate different reports. Highly recommend playing with the prompt to get the best results.

The variables used for governing the thresholds for each metric can be found in the file constants.py. The variables can be modified to govern the number of repositories selected, the weightage given to impact vs complexity and upper-lower bounds used for generating the scores.

The token limit required to not hit maximum content length error can be found in threshold.py.

To Note

The script will only consider code repositories that are authored by the given github user. Contributions made to other repositories will not be considered. This includes contributions made to open source repositories.

This can be explored and implemented in the future.

Credits

Credits to the aider module and the repomap function used goes to paul-gauthier

Checkout his explanation on how to improve GPT4 visibility of code repository using CTags here

Improvements

Highly welcome pull requests and issues to improve the script. Some of the improvements that can be made are:

• Improve the prompts used to generate the reports
• Improve the thresholds for the metrics used to evaluate the repositories
• Explore and implement contributions made to other repositories
• Explore and implement other metrics to evaluate repositories