AgentUI

An Open Source AgentUI for your AgentOS

Agno provides a beautiful UI for interacting with your agents, completely open source, free to use and build on top of. It’s a simple interface that allows you to chat with your agents, view their memory, knowledge, and more.

The AgentOS only uses data in your database. No data is sent to Agno.

The Open Source Agent UI is built with Next.js and TypeScript. After the success of the Agent AgentOS, the community asked for a self-hosted alternative and we delivered!

Get Started with Agent UI

To clone the Agent UI, run the following command in your terminal:

npx create-agent-ui@latest

Enter y to create a new project, install dependencies, then run the agent-ui using:

cd agent-ui && npm run dev

Open http://localhost:3000 to view the Agent UI, but remember to connect to your local agents.

Clone the repository manually

You can also clone the repository manually

git clone https://github.com/agno-agi/agent-ui.git

And run the agent-ui using

cd agent-ui && pnpm install && pnpm dev

Connect your AgentOS

The Agent UI needs to connect to a AgentOS server, which you can run locally or on any cloud provider.

Let’s start with a local AgentOS server. Create a file agentos.py

agentos.py

from agno.agent import Agent
from agno.models.openai import OpenAIChat
from agno.os import AgentOS
from agno.db.sqlite import SqliteDb
from agno.tools.duckduckgo import DuckDuckGoTools
from agno.tools.yfinance import YFinanceTools

agent_storage: str = "tmp/agents.db"

web_agent = Agent(
    name="Web Agent",
    model=OpenAIChat(id="gpt-5-mini"),
    tools=[DuckDuckGoTools()],
    instructions=["Always include sources"],
    # Store the agent sessions in a sqlite database
    db=SqliteDb(db_file=agent_storage),
    # Adds the current date and time to the context
    add_datetime_to_context=True,
    # Adds the history of the conversation to the messages
    add_history_to_context=True,
    # Number of history responses to add to the messages
    num_history_runs=5,
    # Adds markdown formatting to the messages
    markdown=True,
)

finance_agent = Agent(
    name="Finance Agent",
    model=OpenAIChat(id="gpt-5-mini"),
    tools=[YFinanceTools(stock_price=True, analyst_recommendations=True, company_info=True, company_news=True)],
    instructions=["Always use tables to display data"],
    db=SqliteDb(db_file=agent_storage),
    add_datetime_to_context=True,
    add_history_to_context=True,
    num_history_runs=5,
    markdown=True,
)

agent_os = AgentOS(agents=[web_agent, finance_agent])
app = agent_os.get_app()

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

In another terminal, run the AgentOS server:

1. Setup your virtual environment

   Mac

   python3 -m venv .venv
   source .venv/bin/activate
   
2. Install dependencies

   Mac

   pip install -U openai ddgs yfinance sqlalchemy 'fastapi[standard]' agno
   
3. Export your OpenAI key

   Mac

   export OPENAI_API_KEY=sk-***
   
4. Run the AgentOS

   python agentos.py
   

Make sure the serve_agentos_app() points to the file containing your AgentOS app.

View the AgentUI

• Open http://localhost:3000 to view the Agent UI
• Enter the localhost:7777 endpoint on the left sidebar and start chatting with your agents and teams!