Falk

Memory

What the agent “remembers” falls into four categories. Only session memory is configurable; the rest are fixed by design.

What persists

Scope	Storage	Survives restart?	Edited by
Request	None (ephemeral)	No	—
Session	memory or postgres	memory: no, postgres: yes	Agent (during conversation)
Knowledge	Files (semantic_models.yaml, RULES.md, knowledge/*.md)	Yes	Humans (version-controlled)
Feedback	Logfire (optional)	Yes	Agent (traces) + humans (scores)

Session memory

Conversation history and runtime state (last query, pending files) live in the session store.

Option	Use case
memory (default)	Local dev, single process. Works out of the box.
postgres	Production, multi-worker. Requires POSTGRES_URL in .env.

Configure in falk_project.yaml:

session:
  store: memory         # or postgres
  postgres_url: ${POSTGRES_URL}
  schema: falk_session
  ttl: 3600             # seconds before session expires
  maxsize: 500           # max sessions (memory store only)

See Project Config for full options.

Knowledge memory (static)

Loaded at startup from version-controlled files. The agent does not learn from conversations; it reads from:

• semantic_models.yaml — metrics, dimensions, synonyms, gotchas
• RULES.md — behavior, tone, formatting
• knowledge/business.md, knowledge/gotchas.md — when agent.knowledge.enabled: true

See Context for what goes where.

Feedback traces

👍/👎 reactions and traces go to Logfire (if configured). Used for offline improvement — data stewards review low scores and update config files. The agent does not auto-update from feedback.

See Learning & Feedback for the improvement cycle.

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