Slack Agent with User Memory

from textwrap import dedent
from agno.agent import Agent
from agno.db.sqlite import SqliteDb
from agno.memory.manager import MemoryManager
from agno.models.anthropic.claude import Claude
from agno.os.app import AgentOS
from agno.os.interfaces.slack import Slack
from agno.tools.googlesearch import GoogleSearchTools

agent_db = SqliteDb(session_table="agent_sessions", db_file="tmp/persistent_memory.db")

memory_manager = MemoryManager(
    memory_capture_instructions="""\
                    Collect User's name,
                    Collect Information about user's passion and hobbies,
                    Collect Information about the users likes and dislikes,
                    Collect information about what the user is doing with their life right now
                """,
    model=Claude(id="claude-3-5-sonnet-20241022"),
)

personal_agent = Agent(
    name="Basic Agent",
    model=Claude(id="claude-sonnet-4-20250514"),
    tools=[GoogleSearchTools()],
    add_history_to_context=True,
    num_history_runs=3,
    add_datetime_to_context=True,
    markdown=True,
    db=agent_db,
    memory_manager=memory_manager,
    enable_user_memories=True,
    instructions=dedent("""
        You are a personal AI friend in a slack chat, your purpose is to chat with the user about things and make them feel good.
        First introduce yourself and ask for their name then, ask about themeselves, their hobbies, what they like to do and what they like to talk about.
        Use Google Search tool to find latest infromation about things in the conversations
                        """),
    debug_mode=True,
)

agent_os = AgentOS(
    agents=[personal_agent],
    interfaces=[Slack(agent=personal_agent)],
)
app = agent_os.get_app()

if __name__ == "__main__":
    agent_os.serve(app="agent_with_user_memory:app", reload=True)