🔮 LLM Workflow Agent — Hindi-English AI Workflow Assistant
Built for WCHL Hackathon 2025 | Qualified for National Level
Automates everyday tasks via Hindi-English mixed prompts using LLM and APIs.
Handles reminders, emails, todos, weather queries, Google Calendar scheduling with Meet links.
Issue
Description
Task Fragmentation
Users manage reminders, emails, todos, and calendar events separately.
Language Barrier
Existing assistants poorly support mixed Hindi-English commands.
Manual Effort
Daily workflow tasks require repetitive manual intervention.
Objective
Build an AI agent that understands mixed-language commands and automates common workflow tasks efficiently.
💡 Our Solution — LLM Workflow Agent Platform
Component
Description
LLM Engine
LangChain + Google Gemini integration to parse and understand Hindi-English prompts.
Task Agents
Modular task handlers for emails, reminders, todos, weather, and calendar events.
Scheduler
Cron-like task scheduler for reminders and calendar events.
Backend API
Node.js + Express.js API exposing endpoints for frontend and external integrations.
Frontend Dashboard
React + Vite + Tailwind interface for user interaction, chat fallback, and task overview.
Realtime Updates
Socket.IO for live reminder alerts and task notifications.
Feature
Description
🗣️ Mixed-Language Understanding
Supports Hindi-English commands for natural task input.
🔔 Reminders & Alarms
Schedule tasks with live alerts via Socket.IO.
📧 Smart Email Automation
Compose and send emails automatically using Nodemailer.
☀️ Weather Queries
Fetch live weather info for any city.
✅ Todo Management
Create, view, and manage todos seamlessly.
🗓️ Google Calendar Integration
Schedule events with auto-generated Meet links.
💬 LLM Chat Fallback
Handles general conversation if no specific task detected.
Layer
Technology Used
Backend
Node.js, Express.js, JWT, Session Middleware
AI / LLM
LangChain + Google Gemini API
Database
MongoDB (Mongoose)
Email
Nodemailer
Calendar & Meet
Google Calendar API
Frontend
React, Vite, Tailwind CSS
Realtime
Socket.IO
nl_task_automator/
├── backend/
│ ├── agents/ # Task logic modules (email, calendar, reminders, etc.)
│ ├── controllers/ # Express route handlers
│ ├── llm/ # Gemini API integration and prompt handling
│ ├── middlewares/ # Authentication and error handlers
│ ├── models/ # Mongoose database schemas
│ ├── routes/ # API route definitions
│ ├── scheduler/ # Scheduled tasks & reminder management
│ ├── utils/ # Utility functions (date parsing, OAuth setup, etc.)
│ └── server.js # Entry point for the backend server
│
├── frontend/
│ ├── public/ # Static files (index.html, icons, manifest)
│ ├── src/ # React components and pages
│ └── vite.config.js # Frontend bundler configuration
│
├── .gitignore # Git ignore configuration
└── README.md # Project documentation (this file)
Step
Command / Instructions
Backend Setup
cd backend && npm install && cp .env.example .env Edit .env with Mongo URI, JWT secret, Gemini API key, Google OAuth credentials npm run dev
Frontend Setup
cd frontend && npm install && cp .env.example .env Edit .env with VITE_API_BASE_URL=http://localhost:4000 npm run dev
File
Variables
backend/.env
PORT=4000 MONGO_URI=<mongo-uri> JWT_SECRET=<secret> GEMINI_API_KEY=<key> EMAIL=<smtp_email> EMAIL_PASS=<smtp_pass> GOOGLE_CLIENT_ID=<id> GOOGLE_CLIENT_SECRET=<secret> GOOGLE_REDIRECT_URI=http://localhost:4000/api/google/callback
frontend/.env
VITE_API_BASE_URL=http://localhost:4000
# Example command
Create a Google Meet with team Friday 5 PM and email boss
npm run dev # Start development server with nodemon
npm start # Start production server
npm run dev # Start Vite development server
npm run build # Production build
npm run preview # Preview production build
git checkout -b feature/your-feature
git commit -m " feat: add your feature"
git push origin feature/your-feature
© 2025 Jeet Goyal | Built for WCHL Hackathon 2025 (National Level Qualification)