Memory and compaction

1. Session history
2. Context window
3. Compaction
4. Long-term notes

Seshat has three kinds of memory, each with its own job.

1. Session history

Every conversation is saved in a local SQLite database: messages, tool results, token usage and metadata. Sessions survive restarts and can be resumed.

seshat chat --continue          # the most recent session
seshat chat --resume <id>       # a specific one
seshat sessions list

2. The context window and compaction

A model can only read so much at once. Seshat tracks how much of the window a session uses. When it passes a threshold, it compacts: older messages are summarised into a shorter form so the session can go on.

By default, automatic compaction starts at 85% of the usable window and aims for about 50% afterwards. In the Go SDK, turn it on with AutoCompact in ClientConfig.

3. Notes that last

The agent can keep notes across sessions with the memory tools. They form a small knowledge graph of named entities and observations:

Tool	Use
memory_create_entities	Create entities (a person, a project, a decision)
memory_add_observations	Add facts to an entity
memory_search_nodes	Search what is stored
memory_open_nodes	Read specific entities

You can also read and edit memory yourself from the command line:

seshat memory                                          # show user memory
seshat memory --scope project                          # this project's memory
seshat memory --action set --key style --value "short answers, no preamble"
seshat memory --action clear --scope user
seshat memory --action context                         # what would be given to the agent

--scope is user, project or cross (shared across sessions).

Documents and knowledge

Memory is about the conversation and what the agent learns. For large bodies of documents, Seshat has a retrieval layer (chunking, embeddings, hybrid search) in the SDK. It is covered in Retrieval and knowledge.