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Suggestion: WFGY as a debugging overlay for LLMs working on source code #200

@onestardao

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@onestardao

Hi, thanks for curating this awesome list on machine learning for source code.

I would like to propose WFGY as a complementary framework for people using LLMs on code, especially when they wrap them in tools, agents or RAG systems.

WFGY is a text-only “semantic firewall” that you load into an LLM. It helps you diagnose why a code-oriented assistant is failing: retrieval issues, chunking issues, long-chain drift, etc.

Key component:

ProblemMap (WFGY 2.0)
https://github.com/onestardao/WFGY/tree/main/ProblemMap

  • 16 named failure modes for LLM / RAG pipelines.
  • Each entry treats the system as a pipeline (ingestion → embedding → store → retrieval → reasoning), not just a black-box model.
  • This is especially relevant for LLMs that browse codebases through vector stores or code search.

There is also a more formal:

  • WFGY 1.0 PDF explaining the math and structure, and
  • WFGY 3.0 Singularity Demo for long-horizon reasoning tests.

If you consider frameworks that help debug code-oriented LLM tools in scope, WFGY might be worth a short mention. I can open a PR if helpful.

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