AgentOS Dashboard

Comprehensive Agent Dashboard for launching autonomous workflows, startup generation, and financial intelligence.

AgentOS Dashboard – Full Implementation Guide

This guide will walk you through implementing a full-featured AgentOS dashboard system from the provided scaffold. The platform will allow you to launch and manage AI agents, design automations, and build agent-driven workflows with extensible frontend and backend components.

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Prerequisites

• Ubuntu VM (e.g., Oracle Cloud)
• Docker + Docker Compose installed
• Git + VS Code (or CLI)
• OpenAI or Ollama API key (for agents)
• Node.js and Yarn or npm

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Step 1: Backend Setup (FastAPI)

1.1 Navigate to backend and create virtual environment

cd backend
python3 -m venv venv
source venv/bin/activate

1.2 Install Python dependencies

Create requirements.txt with:

fastapi
uvicorn
pydantic
httpx
openai
python-dotenv

Then run:

pip install -r requirements.txt

1.3 Add core FastAPI logic

Edit main.py:

from fastapi import FastAPI
from app.api.routes import router

app = FastAPI()
app.include_router(router)

Edit routes.py:

from fastapi import APIRouter

router = APIRouter()

@router.get("/ping")
def ping():
    return {"status": "AgentOS backend is live"}

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Step 2: Agent Runner (Backend)

Edit agent_runner.py:

import openai
import os

openai.api_key = os.getenv("OPENAI_API_KEY")

def run_agent(prompt: str) -> str:
    response = openai.ChatCompletion.create(
        model="gpt-4",
        messages=[{"role": "user", "content": prompt}]
    )
    return response.choices[0].message.content

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Step 3: Frontend Setup (React + Vite)

3.1 Navigate to frontend

cd ../frontend
npm create vite@latest .
# Choose React + TypeScript
npm install

3.2 Install dependencies

npm install axios react-router-dom

3.3 Create UI components

AgentTerminal.tsx

import { useState } from "react";
import axios from "axios";

export default function AgentTerminal() {
  const [input, setInput] = useState("");
  const [output, setOutput] = useState("");

  const runAgent = async () => {
    const res = await axios.post("/api/agent", { prompt: input });
    setOutput(res.data.response);
  };

  return (
    <div>
      <textarea value={input} onChange={e => setInput(e.target.value)} />
      <button onClick={runAgent}>Run</button>
      <pre>{output}</pre>
    </div>
  );
}

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Step 4: Connect Frontend and Backend via Docker

4.1 Update docker-compose.yml

version: "3.8"

services:
  backend:
    build: ./backend
    ports:
      - "8000:8000"
    volumes:
      - ./backend:/app
    env_file:
      - .env

  frontend:
    build: ./frontend
    ports:
      - "3000:3000"
    volumes:
      - ./frontend:/app
    working_dir: /app
    command: npm run dev

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Step 5: Environment Setup

Edit .env:

OPENAI_API_KEY=sk-...

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Step 6: Run the App

docker-compose up --build

Access the app at:

• Frontend: http://localhost:3000
• Backend: http://localhost:8000/ping

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Next Features

• Add visual workflow builder with React Flow
• Store agents and workflows in Postgres
• Add terminal/console for chatting with multiple agents
• Extend with Discord/Twitter bots
• Enable PDF/Markdown output from agents

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License

MIT – Build your own agent-powered world.