LocalLLaMA user proposes Python research pipeline

Manual extraction-to-markdown provides a high-control alternative to RAG for technical writing, using structured buffers to prevent LLM noise. This move toward multi-stage agentic synthesis pipelines reflects a growing requirement for local-first inference in privacy-sensitive research environments. While high-VRAM hardware remains a baseline for 30B+ parameter models, this modular approach offers the precision necessary for formal academic outputs.