Hefesto – ML-Powered Code Quality Agent with Semantic Analysis

Hey everyone — thanks for checking out Hefesto!

I built this after getting frustrated with traditional linters (flake8, pylint, etc.) that only catch syntax or style issues, not logical drift. In large Python projects, I noticed we often had multiple implementations of the same business rule — all valid syntactically, but inconsistent logically.

Example: apply_discount() in one file used price * 0.8, while another used price * 0.85 for the same user type. Tests passed, linting passed — yet production behavior diverged. Hefesto was designed to detect exactly this kind of semantic mismatch before commit.

How it works:

Parses your codebase, extracts function-level representations.

Uses sentence-transformers to build semantic embeddings for each function.

Compares them to spot near-duplicates with divergent logic.

Optionally uses an OpenAI model to propose normalized fixes or highlight intent mismatches.

Runs as a FastAPI service or CLI (hefesto analyze --project myapp/) integrated with pre-commit or CI/CD.

I’m especially interested in feedback on:

scaling to large repos (>100K LOC),

balancing false positives vs. meaningful matches,

and whether it makes sense to generalize to TypeScript or Go next.

Repo (MIT): https://github.com/artvepa80/Agents-Hefesto

Happy to answer any technical questions or share benchmarks if people are curious.