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How to keep an assistant's preferences across sessions locally with Octop Memory

Store user preferences in a local SQLite file and recall them in later sessions.

Who it is forA developer building a personal assistant who needs it to remember stated preferences between conversations.

The problemEach new session starts without the user's stated preferences, so the assistant repeats questions and ignores earlier choices.

The outcomePreferences are saved to a local database and returned as ranked prompt context when the topic comes up again.

What you need first

  • Python 3.12 or newer
  • pip to install the octop-memory package
  • A database path for local SQLite storage, or a PostgreSQL DSN for server deployments
  • An injected LLMClient only if you want automated extraction, promotion, or page regeneration; manual storage and lexical recall work without a model

Steps

  1. Run pip install octop-memory
  2. Run pip install "octop-memory[cli]" to add the command line tool
  3. Create a Memory object with namespace="demo" and backend_config={"db_path": "./demo.sqlite"}, then call memory.store("User prefers Python for backend services", topic="preferences")
  4. Run octop-memory --db ./demo.sqlite --namespace demo recall "Python" to confirm the stored preference is found
  5. Call MemoryService(memory).recall("Python") in your assistant and inject result.rendered into the prompt

Prompt for your agent

Use the octop-memory repo to store the preference <preference text> in a local SQLite file at ./demo.sqlite under namespace demo. Then recall it with the query <query term> and return the rendered result. Verify that the returned text contains the stored preference.

Caveat. Manual storage and lexical recall need no model, but automated extraction only runs after you inject an LLMClient, since installing the package does not configure one.

Use this in your AI agent

Ask your agent

Using the Deduped MCP, get the setup steps for TencentCloud/octop-memory and "Keep an assistant's preferences across sessions locally"

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