Tier 3 · Agent memory Agent memory · fetched 2026-07-02
Memory-X
An intelligent memory management system designed for medical AI scenarios - a domain-specialized memory design where accuracy and traceability requirements are unusually strict.
View source on GitHubKey takeaways
- 01
Domain constraints (medical) push memory toward strict provenance
- 02
One distinct idea: domain-specific memory schemas
From the archive
Verbatim excerpts mined from our local archive of this repository — the prompts, schemas, and patterns worth stealing.
Memory
Intent → entities → importance: a memory write pipeline
# Step-by-step memory processing pipeline:
intent = memory_ai._detect_intent(message)
entities = memory_ai._recognize_entities(message)
importance = memory_ai._evaluate_importance(intent, entities)
retrieved = memory_manager.search_long_term_memory(message)
# Example (medical assistant): message = "I'm allergic to penicillin,
# and diabetes runs in my family" -> entities {allergy, family history}
# -> high importance -> stored to long-term memory. [translated] A medical-domain memory manager where every message passes an intent/entity/importance gate before anything is committed to long-term storage.
demos/analysis/debug_memory.py