[MRG] fix typos

[HuaizhengZhang]

User description

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PR Type

enhancement

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Description

• Improved user prompts to provide clearer instructions for resuming steps and providing requirements.
• Updated step descriptions to better reflect the actions being performed by various agents.
• Enhanced debugging status messages to specify the role of the MLE Debug Agent.

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Changes walkthrough 📝

	Relevant files
Enhancement	baseline.py Improve user interaction and step descriptions in baseline workflow mle/workflow/baseline.py Improved user prompts for clarity. Updated step descriptions for better understanding. Enhanced debugging status messages. +8/-6

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[github-actions]

PR Reviewer Guide 🔍

⏱️ Estimated effort to review: 2 🔵🔵⚪⚪⚪

🧪 No relevant tests

🔒 No security concerns identified

⚡ Key issues to review String Formatting The string formatting in line 37 might cause a runtime error if cache is not a string. Ensure cache is converted to string or use a different method to format the message.

[github-actions]

PR Code Suggestions ✨

Category	Suggestion	Score
Enhancement	Ensure user input is within a valid range before processing Add a check to ensure that the user input for 'step' is within the valid range before converting it to an integer. mle/workflow/baseline.py [36-40] step = ask_text(f"MLE has finished the following steps: \n{cache}\n" "You can pick a step from 1 to {cache} to resume\n" "(or ENTER to continue the workflow)") -if step: +if step and 1 <= int(step) <= cache.current_step(): step = int(step) Suggestion importance[1-10]: 9 Why: This suggestion adds a necessary validation step to ensure user input is within a valid range, preventing potential runtime errors and improving robustness.	9
	Standardize the check for debugging status to be case insensitive Refactor the debugging loop to handle the 'is_debugging' condition more robustly by converting the string to lowercase. mle/workflow/baseline.py [98-100] -if is_debugging == 'true' or is_debugging == 'True': +if is_debugging.lower() == 'true': with console.status("MLE Debug Agent is executing and debugging the code..."): debug_report = debugger.analyze(code_report) Suggestion importance[1-10]: 8 Why: This suggestion standardizes the check for the debugging status by making it case insensitive, which increases the robustness of the condition check.	8
	Improve user input handling for requirements Replace the direct use of 'ask_text' with a validation loop to handle empty or invalid inputs more gracefully. mle/workflow/baseline.py [58-61] -ml_requirement = ask_text("Please provide your requirement") -if not ml_requirement: - print_in_box("The user's requirement is empty. Aborted", console, title="Error", color="red") - return +while True: + ml_requirement = ask_text("Please provide your requirement") + if ml_requirement: + break + print_in_box("The user's requirement cannot be empty. Please provide a valid input.", console, title="Error", color="red") Suggestion importance[1-10]: 7 Why: The suggestion improves user input handling by ensuring that a valid requirement is provided, enhancing user experience and preventing premature termination of the function.	7
Possible bug	Improve string formatting for clarity and correctness Replace the string interpolation with a formatted string to avoid potential type errors and improve readability. mle/workflow/baseline.py [36-38] step = ask_text(f"MLE has finished the following steps: \n{cache}\n" - "You can pick a step from 1 to {cache} to resume\n" + f"You can pick a step from 1 to {len(cache)} to resume\n" "(or ENTER to continue the workflow)") Suggestion importance[1-10]: 8 Why: The suggestion correctly identifies a potential issue with string formatting and improves it by using the length of the cache, which enhances both readability and correctness.	8