Rebase our benchmark to the current main of Princeton NLP

[kgilpin]

https://github.com/princeton-nlp/SWE-bench/commits/main/

[github-actions[bot]]

Title: Rebase Benchmark to Current Main of Princeton NLP's SWE-bench

Problem: The benchmark project, navie-benchmark, needs to be updated to align with the latest changes in the main branch of the SWE-bench repository maintained by Princeton NLP. This update will ensure that our benchmarks are using the most relevant and up-to-date datasets and code, maintaining compatibility and accuracy in evaluations.

Analysis: To seamlessly integrate changes from the main branch of the Princeton NLP's SWE-bench, we need to perform a rebase of our existing codebase. This will involve pulling changes from the upstream repository and resolving any conflicts that may arise due to differences in the code. This ensures that we have all the latest features, bug fixes, and improvements made in the upstream repository. Consequently, this will also involve reviewing changes that may affect the current implementation in terms of dependencies, dataset configurations, and pipeline adjustments.

Proposed Changes:

1. Repository Configuration:

   • Ensure that the Princeton NLP SWE-bench repository is added as a remote in the local Git configuration. If not already present, add it using git remote add.

2. Rebase Process:

   • Fetch the latest changes from the upstream repository: Use git fetch upstream to get the updates from the main branch of the SWE-bench.
   • Start the rebase process: Perform git rebase upstream/main, which will apply the new commits from the main branch onto the current branch.
   • Conflict Resolution: If there are any conflicts during the rebase, manually review each conflicting file, finding a resolution that aligns with both updates and pre-existing custom changes.

3. Dependency Management:

   • Review all Python dependencies related to the project, especially those that concern data loading and evaluation, to ensure compatibility with any updated versions.
   • Update scripts and Jupyter notebooks, specifically those involving dataset handling and evaluations, checking for compatibility with the new updates. This may involve modifications to how datasets are loaded or evaluated.

4. Testing and Verification:

   • Execute all available tests in the project to ensure that the benchmark functionality works correctly after the rebase.
   • Validate that the datasets and evaluations are producing expected results consistent with previous benchmarks. Also, run sequence diagrams to identify if evaluation flows remain accurate.

5. Documentation:

   • Update any relevant documentation in the README or related project files, indicating changes, updates, or necessary steps that came with the rebase, especially concerning any modifications in input/output parameters or dataset formats.

Performing these steps will ensure that navie-benchmark aligns with the latest improvements, features, and datasets of the SWE-bench main branch.