Memory

Give an agent a conversation buffer that persists across turns.

Memory allows an agent to remember previous conversations.

Instead of treating every request as a new conversation, the agent can retain context and generate more natural responses.

Create a Memory#

Python

from abagentsdk import Memory

memory = Memory()

Use Memory with an Agent#

agent.py

from abagentsdk import Agent, Memory

memory = Memory()

agent = Agent(
    name="Assistant",
    instructions="You are a helpful AI assistant.",
    model="gemini-2.5-flash",
    memory=memory
)

Your agent will now remember previous messages during the conversation.

Example#

Python

agent.run("My name is Abu Bakar.")

response = agent.run("What is my name?")

print(response.content)

Example Output

Output

Your name is Abu Bakar.

Clearing Memory#

Create a new Memory instance to start a fresh conversation.

Python

memory = Memory()

When to Use Memory#

Memory is useful for:

AI Chatbots
Customer Support
Personal Assistants
Research Assistants
Voice Assistants

Best Practices#

Create one memory instance for each conversation.
Reuse the same memory object during the conversation.
Create a new memory instance for a new conversation.

Next Step#

Continue to Tools.