FishMem

Cookbooks

End-to-end recipes that combine add, search, and scoping into working agents with memory.

A cookbook is a complete recipe, not a single API call. Each one wires the add and search operations together with scoping to build a real agent that remembers across sessions. Copy the example, swap in your own LLM call and IDs, and ship.

Recipes

The pattern every recipe follows

  1. Add durable facts during the conversation — after each meaningful turn or resolved task, write what's worth remembering. Let FishMem extract and reconcile facts (infer: true), or store rules verbatim (infer: false).
  2. Search relevant memories before you answer — retrieve the few memories that bear on the current query and inject them into your prompt, instead of stuffing the entire history.
  3. Scope per user, agent, or run for isolation — bind every memory to a user_id, agent_id, and/or run_id so one customer, project, or session never sees another's facts.

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