[P] Unix philosophy for ML pipelines: modular, swappable stages with typed contracts

We built an open-source prototype that applies Unix philosophy to retrieval pipelines. Each stage (PII redaction, chunking, dedup, embeddings, eval) is its own plugin with a typed contract, like pipes between Unix tools. The motivation: we swapped a chunker and retrieval got worse, but could not isolate whether it was the chunking or something breaking downstream. With each stage independently swappable, you change one option, re-run eval, and compare precision/recall directly. ```python Feature("docs__pii_redacted__chunked__deduped__embedded__evaluated", options={ "redaction_method": "presidio", "chunking_method": "sentence", "embedding_method": "tfidf", }) ``` Each `__` is a stage boundary. Swap any piece, the rest stays the same. Still a prototype, not production. Looking for feedback on whether the design assumptions hold up. Repo: [https://github.com/mloda-ai/rag_integration](https://github.com/mloda-ai/rag_integration)