Agent Memory

Understanding how agents maintain context and learn

Memory lets agents remember conversations and learn from past interactions. Without memory, every message is like starting fresh.

Diagram

Quick Start

python

from praisonaiagents import Agent

# Enable memory with one parameter
agent = Agent(
    instructions="You are a personal assistant",
    memory=True  # Remember conversations
)

agent.start("My name is Alex and I love Python")
# Later...
agent.start("What's my name?")  # Agent remembers: "Alex"

Types of Memory

Diagram

Short-Term

Remembers current chat

Long-Term

Persists across sessions

Knowledge

Access to documents

Memory Options

Basic Memory (Conversation)

python

agent = Agent(
    instructions="You are helpful",
    memory=True  # Remembers the conversation
)

Long-Term Memory (Persistent)

python

agent = Agent(
    instructions="You are a personal assistant",
    memory={
        "provider": "sqlite",  # Store in database
        "db_path": "memory.db"
    }
)

Knowledge Memory (Documents)

python

agent = Agent(
    instructions="Answer from documents",
    knowledge=["docs/"],  # Load documents
    memory=True
)

How Memory Works

Diagram

Step	What Happens
Input	You send a message
Retrieve	Agent checks memory for context
Process	Combines memory + new input
Respond	Generates informed response
Save	Stores important info for later

Complete Example

python

from praisonaiagents import Agent

# Personal assistant with memory
assistant = Agent(
    name="PersonalAssistant",
    instructions="""You are a personal assistant.
    Remember user preferences and past conversations.
    Be helpful and personalized.""",
    memory=True
)

# First conversation
assistant.start("I prefer short, bullet-point answers")
assistant.start("My favorite programming language is Python")

# Later conversation - agent remembers!
assistant.start("Explain how to read a file")
# Agent will give short, bullet-point answer about Python

Multi-Agent Memory

Agents can share memory or have private memory:

Diagram

python

from praisonaiagents import Agent, AgentTeam

# Agents with shared memory
researcher = Agent(instructions="Research topics", memory=True)
writer = Agent(instructions="Write summaries", memory=True)

team = AgentTeam(
    agents=[researcher, writer],
    memory=True  # Shared team memory
)

Best Practices

Start Simple

Use memory=True first, add complexity later

Be Specific

Tell the agent what to remember in instructions

Use Knowledge

For documents, use knowledge= not memory

Test Memory

Verify the agent remembers correctly

Next: Multi-Agent Systems

Learn how multiple agents work together.