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🤖 Multi-Agent Task Orchestrator

An intelligent AI-powered task orchestration system that uses multiple specialized agents to collaboratively plan, execute, and review complex tasks. Built with LangGraph, FastAPI, and React.

Multi-Agent Orchestrator FastAPI React MongoDB

✨ Features

🎯 Multi-Agent Orchestration

  • Planner Agent: Creates step-by-step execution plans
  • Executor Agent: Performs tasks based on the plan
  • Critic Agent: Reviews and validates outputs
  • Supervisor Agent: Orchestrates the entire workflow

🔐 Authentication & Security

  • Dual Authentication: Username/password and Google OAuth
  • JWT Token Management: Secure 24-hour sessions
  • User Isolation: Each user's data is completely separate
  • Password Security: Bcrypt hashing with strength validation

💬 Chat Interface

  • Real-time Conversations: Seamless interaction with AI agents
  • Session Management: Save and resume conversations
  • Chat History: Access all previous conversations
  • Beautiful UI: Modern dark theme with smooth animations

🗄️ Data Persistence

  • MongoDB Integration: All conversations stored securely
  • User Profiles: Track user activity and preferences
  • Session Filtering: Users see only their own sessions

🛠️ Tech Stack

Backend

  • Framework: FastAPI (Python)
  • AI Orchestration: LangGraph
  • LLM Providers: OpenAI, Groq, Google Gemini
  • Database: MongoDB (Motor async driver)
  • Authentication: JWT, OAuth 2.0
  • Security: Bcrypt, python-jose

Frontend

  • Framework: React 18 + Vite
  • Styling: Tailwind CSS
  • Routing: React Router v6
  • State Management: Context API
  • UI/UX: Custom components, smooth animations

🚀 Quick Start

Prerequisites

  • Python 3.11+
  • Node.js 18+
  • MongoDB 6.0+
  • OpenAI/Groq/Gemini API Key

Backend Setup

  1. Clone the repository
git clone https://github.com/nivas2823/multi-agent-orchestrator.git
cd multi-agent-orchestrator
  1. Install Python dependencies
cd backend
pip install -r requirements.txt
  1. Configure environment variables
cp .env.example .env
# Edit .env with your API keys

Required environment variables:

# LLM Configuration
GROQ_API_KEY=your_groq_key
OPENAI_API_KEY=your_openai_key
GEMINI_API_KEY=your_gemini_key
LLM_PROVIDER=groq
LLM_MODEL=llama-3.3-70b-versatile

# MongoDB
MONGODB_URL=mongodb://localhost:27017
MONGODB_DB_NAME=multi_agent_system

# JWT Authentication
JWT_SECRET_KEY=your_secret_key_here

# Google OAuth (Optional)
GOOGLE_CLIENT_ID=your_client_id
GOOGLE_CLIENT_SECRET=your_client_secret
GOOGLE_REDIRECT_URI=http://localhost:8000/api/auth/google/callback
FRONTEND_URL=http://localhost:5173

Run the backend

uvicorn app.main:app --reload

Backend will be available at http://localhost:8000

Frontend Setup

  1. Install dependencies

cd frontend npm install

  1. Start development server

npm run dev

Frontend will be available at http://localhost:5173

📚 API Documentation

Once the backend is running, access:

About

An intelligent task orchestration system powered by multiple AI agents. Features planner, researcher, executor, and critic agents working together using LangGraph. Built with FastAPI backend, React frontend, JWT authentication, MongoDB persistence, and Google OAuth integration.

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