Agent with User Memory

from textwrap import dedent
from agno.agent import Agent
from agno.app.slack.app import SlackAPI
from agno.memory.v2.db.sqlite import SqliteMemoryDb
from agno.memory.v2.manager import MemoryManager
from agno.memory.v2.memory import Memory
from agno.models.anthropic.claude import Claude
from agno.storage.sqlite import SqliteStorage
from agno.tools.googlesearch import GoogleSearchTools

agent_storage = SqliteStorage(
    table_name="agent_sessions", db_file="tmp/persistent_memory.db"
)
memory_db = SqliteMemoryDb(table_name="memory", db_file="tmp/memory.db")

memory = Memory(
    db=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"),
    ),
)


# Reset the memory for this example
memory.clear()

personal_agent = Agent(
    name="Basic Agent",
    model=Claude(id="claude-sonnet-4-20250514"),
    tools=[GoogleSearchTools()],
    add_history_to_messages=True,
    num_history_responses=3,
    add_datetime_to_instructions=True,
    markdown=True,
    memory=memory,
    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
        You may sometimes recieve messages prepenned with group message when that is the message then reply to whole group instead of treating them as from a single user
                        """),
    debug_mode=True,
    add_state_in_messages=True,
)


slack_api_app = SlackAPI(
    agent=personal_agent,
    name="Agent with User Memory",
    app_id="agent_with_user_memory",
    description="A agent with user memory that can chat with the user about things and make them feel good.",
)
app = slack_api_app.get_app()

if __name__ == "__main__":
    slack_api_app.serve("agent_with_user_memory:app", port=8000, reload=True)