Notes (Memory)

Sidebar → Notes → New

A note repository is the agent's long-term memory: a vector store the agent can write to and search via tool calls. Use it to recall facts across conversations — user preferences, project context, prior decisions — without bloating the system prompt.

Prerequisites

An embedding model is required first: sidebar → Embedding Models → New. See Models.

Configuration

Field	Description
Name	Display name for this notebook
Embedding	Embedding model used for semantic search (OpenAI, Google, Ollama, Cohere, VoyageAI)

How It Works

1. Add — The agent inserts text via the note_add tool, or you add chunks manually in the UI
2. Embed — Each chunk is converted to a vector
3. Search — On retrieval, relevant notes are ranked by semantic similarity with time-decay weighting (recent entries score higher)
4. Dedup — Near-duplicate inserts are auto-merged so the store doesn't bloat

Assignment

Notes can be assigned at multiple scopes (most specific wins):

• Default per agent — every session/channel using this agent inherits it
• Per session — override on the chat session
• Per channel — override per channel

Notes vs Wiki vs Memory

Concept	Owner	Best for
Notes	Agent (auto-write)	Free-form facts the agent recalls semantically
Wiki	Human-curated (with optional embeddings)	Structured knowledge pages with titles + tags
Memory	Background MemoryLLM	Distilled long-term knowledge from past conversations