Worked on the vllm-project/llm-compressor repository to enhance reliability in the AutoWrapper component by addressing a runtime argument inference bug related to self-assignment handling. Applied advanced AST manipulation techniques in Python to ensure variables that are both read and written within the same statement are correctly managed, preventing torch.fx runtime errors. Developed and integrated targeted tests to verify the fix and guard against future regressions, with all changes traceable to issue #1616. Focused on improving the stability of the LLM compression pipeline, emphasizing thorough testing and precise bug resolution to maintain correctness and robustness in the codebase.