working regex

[SilenNaihin]

Background

Adding regex flagging function for actions

PR Quality Checklist

• I have run the following commands against my code to ensure it passes our linters:

  black . --exclude test.py
  isort .
  mypy .
  autoflake --remove-all-unused-imports --recursive --ignore-init-module-imports --ignore-pass-after-docstring --in-place agbenchmark

[github-actions]

PR Analysis

• 🎯 Main theme: Adding regex flagging function for actions
• 📝 PR summary: This PR introduces a regex flagging function to identify actions in logs. It includes changes to the agent_action_regex.py file to define what constitutes an action for different agents. It also modifies the combined_data.ipynb notebook to use this function and write flagged actions to JSON files.
• 📌 Type of PR: Enhancement
• 🧪 Relevant tests added: No
• 🔒 Security concerns: No security concerns found

PR Feedback

• 💡 General suggestions: The PR seems to be well-structured and the changes are logically grouped. The code is generally clean and easy to understand. However, there are some areas where the code could be improved for readability and maintainability. It would be beneficial to add some tests to ensure the new functionality works as expected.

• 🤖 Code feedback:

  • relevant file: paper/agent_action_regex.py
    suggestion: Consider refactoring the is_action_agent function to use a dictionary mapping agents to their corresponding functions. This would eliminate the need for the if-elif chain and make the code more maintainable. [important]
    relevant line: "+ if agent == "auto-gpt":"

  • relevant file: paper/agent_action_regex.py
    suggestion: The is_action_general function currently uses a regular expression to search for specific keywords in the log. This could potentially lead to false positives if these keywords are part of other words. Consider splitting the log into words and checking if any of the keywords are in the list of words. [medium]
    relevant line: "+ return bool("

  • relevant file: paper/combined_data.ipynb
    suggestion: The code currently writes to a JSON file within a loop. This could be inefficient if the number of iterations is large. Consider collecting all the data first and then writing it to the file. [medium]
    relevant line: "+ with open(f'{challenge}/{agent}/flagged_actions.json', 'w') as f:"

  • relevant file: paper/agent_action_regex.py
    suggestion: The is_action_agent function currently prints a message and returns False if the log is None. Consider raising an exception instead to make it clear that this is an error condition. [medium]
    relevant line: "+ if log is None:"

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