Agent with User Memory

Discord agent with agentic memory and web search using SqliteDb.

Code

agent_with_user_memory.py

from textwrap import dedent

from agno.agent import Agent
from agno.db.sqlite import SqliteDb
from agno.integrations.discord import DiscordClient
from agno.models.google import Gemini
from agno.tools.websearch import WebSearchTools

db = SqliteDb(db_file="tmp/discord_client_cookbook.db")

personal_agent = Agent(
    name="Basic Agent",
    model=Gemini(id="gemini-2.0-flash"),
    tools=[WebSearchTools()],
    add_history_to_context=True,
    num_history_runs=3,
    add_datetime_to_context=True,
    markdown=True,
    db=db,
    enable_agentic_memory=True,
    instructions=dedent("""
        You are a personal AI friend of the user, 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 DuckDuckGo search tool to find latest information about things in the conversations
                        """),
    debug_mode=True,
)

discord_agent = DiscordClient(personal_agent)
if __name__ == "__main__":
    discord_agent.serve()

Usage

1. Set up your virtual environment

   Mac

   uv venv --python 3.12
   source .venv/bin/activate
   

   uv venv --python 3.12
   .venv\Scripts\activate
   
2. Set your API keys

   export GOOGLE_API_KEY=xxx
   export DISCORD_BOT_TOKEN=xxx
   
3. Install dependencies

   uv pip install -U agno google-genai ddgs sqlalchemy discord.py
   
4. Run Agent

   Save the code above as agent_with_user_memory.py, then run:

   python agent_with_user_memory.py