Engineer Daily Coach (EDC)

EDC is a personalized daily learning platform delivered via Telegram, designed for engineering, preparing for top-tier tech interviews (Amazon, Uber, Flipkart, etc.).

🚀 Features

• Daily Lessons: 15-20 min modules covering DSA, System Design, and AI.
• Saturday Revision: Consolidated weekly content for better retention.
• Sunday Deep Dives: Intensive 30-40 min deep dives into complex topics.
• Multi-AI Powered: Content generated using Groq (Llama 3), OpenAI (GPT-4o), or Google Gemini.
• Automatic Fallback: Intelligent switching between AI providers (Groq -> Gemini -> OpenAI) to ensure delivery.
• Message Chunking: Automatically splits long AI lessons into multiple Telegram messages to bypass the 4096-character limit.
• Personalized: Content focus adjusts based on your Experience, Role, Weak Topics, and Strong Topics.
• Automated Delivery: Scheduled delivery at 06:00 PM IST daily.

🛠 Tech Stack

• Backend: Node.js, Express.js
• Database: MongoDB (Mongoose)
• AI: Groq API, OpenAI API, Google Gemini API
• Messaging: Telegram Bot API (Telegraf)
• Scheduling: node-cron
• Validation: Zod
• Logging: Winston, Morgan

📁 Project Structure

src/
├── config/           # Environment variables & validation
├── database/         # Connection and Mongoose models
├── modules/
│   ├── users/        # User profiles & Personalization Engine
│   ├── progress/     # Progress tracking
│   ├── curriculum/   # Curriculum management logic
│   ├── openai/       # LLM Service (Unified Groq/Gemini/OpenAI) and Prompt Builders
│   ├── telegram/     # Telegram Bot integration (with Message Chunking)
│   ├── scheduler/    # node-cron job definitions
├── shared/           # Utils, Logger, Error Handling
├── app.js            # Express application setup
└── server.js         # Entry point

⚙️ Setup (Standalone Use)

1. Clone the repository
2. Install dependencies:

   npm install

3. Configure Environment: Create a .env file based on .env.example:

   PORT=3000
   MONGODB_URI=your_mongodb_connection_string
      
   # AI Provider Configuration
   AI_PROVIDER=groq # 'groq', 'gemini', or 'openai'
      
   # Groq (Free & Fast - Recommended)
   GROQ_API_KEY=your_groq_key
   GROQ_MODEL=llama-3.3-70b-versatile
      
   # Google Gemini (Free Tier)
   GEMINI_API_KEY=your_gemini_key
   GEMINI_MODEL=gemini-pro
   GEMINI_API_VERSION=v1
      
   # OpenAI (Paid)
   OPENAI_API_KEY=your_openai_key
   OPENAI_MODEL=gpt-4o-mini
      
   TELEGRAM_BOT_TOKEN=your_telegram_bot_token
   NODE_ENV=development

4. Run the application:
   • Development: npm run dev
   • Production: npm start

📦 NPM Package Usage

You can also use EDC as a dependency in your own project:

1. Install the package:

   npm install engineer-daily-coach

2. Initialize in your code: Ensure you have the required environment variables (see .env.example) set in your process environment.

   const edc = require('engineer-daily-coach');
   
   async function startMyBot() {
     try {
       // Starts the scheduler, bot, and health server
       await edc.start({
         port: 3000 // optional health check port
       });
       console.log("EDC Service Started!");
     } catch (err) {
       console.error("Failed to start EDC:", err);
     }
   }
   
   startMyBot();

🧠 AI Priority & Fallback Logic

The system uses a unified LLMService to manage content generation:

• Priority: Controlled by the AI_PROVIDER environment variable.
• Fallback: If the primary provider fails (e.g., Quota exceeded or 404), the system automatically cycles through other configured providers to ensure the lesson is delivered.

📡 Telegram Bot Commands

• /start: Initialize the bot interaction.
• /register: Interactive profile setup (Experience, Role, Targets, Weak/Strong Topics).
• /profile: View your current profile settings.
• /status: Check your current learning progress (Day count).
• /reset: Delete your profile to restart the registration.

🧪 Helper Scripts

• Diagnostic Gemini: node scripts/check-gemini.js (Check which Gemini models are available).
• Seed & Test: TELEGRAM_ID=your_id node scripts/seed-and-test.js (Manually trigger a lesson delivery for testing).

🚀 Deployment

The project is ready for deployment on Render.

• Build Command: npm install
• Start Command: npm start
• Ensure all Environment Variables are configured in the Render dashboard.

⚖️ License

ISC