Memory

Memory examples enact the trade-off between recall, cost, and latency. Sources under examples/memory/.

Name	Scenario	Source
`memory_types`	Run the same 5-turn conversation through `Buffer`, `Window(2)`, and `TokenBufferMemory(200)` — watch which ones still pass the recall test.	src
`memory_summary_buffer`	10-turn customer support thread — older turns get LLM-summarized into a running summary so the agent can still recall the original order ID.	src
`memory_knowledge_graph`	Bot learns facts about Project Atlas through conversation, then is asked to recall them — the KG memory stores triples and the agent queries them.	src

How to run

COGNIS_PROVIDER=ollama COGNIS_OLLAMA_MODEL=llama3.1 \
  cargo run -p cognis-examples --example memory_types

First time? memory_types shows all three variants on the same conversation, side by side.
Long sessions? memory_summary_buffer is the right default — buffer keeps recent turns, summary keeps the long-tail facts.
Knowledge-graph use cases? memory_knowledge_graph for triple-shaped memory across sessions.

All variants explained, when to reach for each.

Memory + persistence in a real chat backend.