Magnolia: A Persistent-Memory Agent Framework for Computational Chemistry

Magnolia is a persistent‑memory AI agent framework designed for computational chemistry. It integrates protocols such as docking, quantum chemistry, and molecular dynamics with lab notebooks and LLM‑augmented chat logs, using a three‑tier memory system to capture, distill, and promote learnings into project‑tier entries and cross‑project rules. In four case studies, Magnolia tracked 317 runs, produced 116 project‑tier entries, and promoted four cross‑project rules, demonstrating that runs with memory passed all checks while memory‑less runs failed.

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• llms
• agents
• efficiency