Work with Memory

This tutorial shows you how to enable and use DeerFlow’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.