Module
Long-Term Memory
Short-term memory is ephemeral — it captures what happened in this conversation, but not what the agent knows about the world. This module covers the persistent knowledge graph layer: how to classify and store entities using the POLE+O model, why a graph outperforms a vector database for multi-hop knowledge retrieval, and how the entity extraction pipeline automatically populates this layer from conversation messages.
By the end of this module, you will:
- Classify any business domain using the POLE+O entity model
- Explain why multi-hop graph traversal answers questions that vector databases cannot
- Configure the three-stage entity extraction pipeline (spaCy → GLiNER2 → LLM fallback)
- Store, search, and retrieve entities using the long-term memory API
- Run the extraction pipeline against your own instance and follow
EXTRACTED_FROMback to the message an entity came from