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Memory allows agents to maintain conversation context across multiple messages within a session. This enables natural, contextual conversations where the agent remembers previous interactions.

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Quick Start

from lyzr import Studio

studio = Studio(api_key="your-api-key")

# Create agent with memory
agent = studio.create_agent(
    name="Conversational Bot",
    provider="gpt-4o",
    role="Helpful assistant",
    goal="Have natural conversations",
    instructions="Remember context from previous messages",
    memory=30  # Remember last 30 messages
)

# Start a conversation
session_id = "user_123_session"

agent.run("My name is Alice", session_id=session_id)
agent.run("I'm interested in Python programming", session_id=session_id)
response = agent.run("What's my name and what am I interested in?", session_id=session_id)

# Agent remembers: "Your name is Alice and you're interested in Python programming"

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How Memory Works

  1. Messages are stored per session using the session_id
  2. Context is maintained across multiple agent.run() calls
  3. Recent messages are included in the agent’s context window
  4. Older messages are automatically pruned based on max_messages

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Memory Configuration

ParameterRangeDescription
memory1-50Number of recent messages to remember

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At Agent Creation

agent = studio.create_agent(
    name="Bot",
    provider="gpt-4o",
    memory=30  # Keep last 30 messages
)

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On Existing Agent

agent = agent.add_memory(max_messages=50)

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Session Management

Memory is scoped to sessions. Use session_id to maintain separate conversations: 
# User 1's conversation
agent.run("Hello", session_id="user_1_session")
agent.run("My name is Bob", session_id="user_1_session")

# User 2's conversation (separate context)
agent.run("Hello", session_id="user_2_session")
agent.run("My name is Carol", session_id="user_2_session")

# Each session has its own memory

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Use Cases

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Customer Support

agent = studio.create_agent(
    name="Support Bot",
    provider="gpt-4o",
    role="Customer support",
    memory=50
)

session = "support_12345"
agent.run("I bought a laptop last week", session_id=session)
agent.run("The screen is flickering", session_id=session)
agent.run("What solutions do you have?", session_id=session)
# Agent knows: bought laptop last week, screen flickering

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Multi-Turn Tasks

agent = studio.create_agent(
    name="Research Assistant",
    provider="gpt-4o",
    role="Research assistant",
    memory=50
)

session = "research_session"
agent.run("Let's research climate change", session_id=session)
agent.run("Focus on renewable energy solutions", session_id=session)
agent.run("What are the key findings?", session_id=session)

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Tutoring

agent = studio.create_agent(
    name="Math Tutor",
    provider="gpt-4o",
    role="Math tutor",
    memory=30
)

session = "lesson_1"
agent.run("I'm learning algebra", session_id=session)
agent.run("I struggle with quadratic equations", session_id=session)
agent.run("Can you give me a practice problem?", session_id=session)
# Tutor remembers: algebra, struggles with quadratics

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Next Steps

Agent Memory

Learn all memory configuration options