Work with Memory

This tutorial shows you how to enable and use PengBao AI’s memory system so the agent remembers important information about you across multiple sessions.

Enable memory

In config.yaml:


memory:
  enabled: true
  injection_enabled: true
  max_injection_tokens: 2000
  debounce_seconds: 30

How memory works

Memory works automatically through MemoryMiddleware:

First conversation: tell the agent about your preferences, project, or background.
Automatic learning: the agent extracts and saves important facts in the background.
Future conversations: memory facts are automatically injected into the system prompt — the agent does not need you to repeat context.

Example

First conversation:


I am a Python backend developer primarily using FastAPI and PostgreSQL.
My team follows PEP 8 and prefers type annotations everywhere.
Please remember this for future code suggestions.

Later conversation (no need to repeat background):


Help me write a user authentication module

The agent will automatically produce FastAPI-style code with type annotations.

Inspect memory

Memory is stored in backend/.deer-flow/memory.json:


cat backend/.deer-flow/memory.json

Per-agent memory

When a custom agent is active, it maintains its own memory file at:


backend/.deer-flow/agents/{agent_name}/memory.json

This keeps each agent’s learned knowledge separate.