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# EduPlannerBotAI
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**EduPlannerBotAI** is a Telegram bot built with `aiogram 3.x` and powered by a multi-level LLM architecture. It generates personalized study plans, exports them to PDF/TXT, and sends reminders as Telegram messages. All data is stored using TinyDB (no other DBs supported).
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**EduPlannerBotAI** is a Telegram bot built with `aiogram 3.x` and powered by a revolutionary multi-level LLM architecture. It generates personalized study plans, exports them to PDF/TXT, and sends reminders as Telegram messages. All data is stored using TinyDB (no other DBs supported).
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> **Note:** All code comments and docstrings are in English for international collaboration and code clarity. All user-facing messages and buttons are automatically translated to the user's selected language.
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## 🚀 What's New in v4.0.0
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- **🆕 Multi-Level LLM Architecture**: OpenAI → Groq → Local LLM → Fallback Plan
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- **🆕 Local LLM Integration**: TinyLlama 1.1B model for offline operation
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- **🆕 Guaranteed Availability**: Bot works even without internet connection
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- **🆕 Enhanced Fallback System**: Robust error handling and service switching
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- **🆕 Improved Plan Quality**: Professional-grade study plan templates
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- **🆕 Offline Translation**: Local LLM supports offline text translation
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## 📌 Features
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- 📚 Generate personalized study plans using multi-level LLM architecture
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- 📝 Export study plans to PDF/TXT
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-Send reminders as Telegram messages for each study step
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- 🗄️ Store data using TinyDB (no SQL/other DBs)
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- 🌐 Multilingual: English, Russian, Spanish — all messages, buttons, and files are translated in real time using LLMs
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- 🏷️ All keyboards are always shown with a short message, ensuring buttons are reliably displayed
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- ❌ No empty or invisible messages — all user-facing text is always non-empty (prevents Telegram errors)
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- 🔄 Language selection buttons are not translated, so the language filter works correctly
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- 🤖 If translation is not possible, the original English text is sent
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- 🧩 Simple, maintainable, idiomatic codebase — ready for extension
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- 🚀 **NEW**: Local LLM integration for offline operation and guaranteed availability
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- 📚 **Multi-Level LLM Architecture**: Generate personalized study plans using OpenAI, Groq, Local LLM, or fallback templates
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- 📝 **Export Options**: Save plans as PDF or TXT files
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-**Smart Reminders**: Receive Telegram notifications for each study step
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- 🗄️ **Lightweight Storage**: TinyDB-based data storage (no SQL required)
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- 🌐 **Multilingual Support**: English, Russian, Spanish with real-time LLM translation
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- 🏷️ **Reliable UI**: All keyboards displayed with proper messages (no Telegram errors)
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- 🔄 **Smart Language Handling**: Language selection works correctly without translation
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- 🤖 **Graceful Fallbacks**: Original text sent if translation fails
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- 🧩 **Extensible Codebase**: Clean, maintainable code ready for extensions
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- 🚀 **Offline Operation**: Local LLM ensures 100% availability
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- 🔒 **Privacy First**: Local processing keeps your data secure
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## 🆕 Multi-Level LLM Architecture
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## 🏗️ Multi-Level LLM Architecture
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The bot now features a sophisticated multi-level fallback system that ensures reliable service even when external APIs are unavailable:
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The bot features a sophisticated 4-tier fallback system that ensures reliable service even during complete internet outages:
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### LLM Processing Chain
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### 🎯 LLM Processing Chain
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1. **OpenAI GPT** (Priority 1) - Primary model for generating study plans
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2. **Groq** (Priority 2) - Secondary model, used if OpenAI is unavailable
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3. **Local LLM** (Priority 3) - Local TinyLlama 1.1B model for offline operation
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4. **Fallback Plan** (Priority 4) - Predefined high-quality study plan template
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| Priority | Service | Description | Use Case |
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|----------|---------|-------------|----------|
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| **1** | **OpenAI GPT** | Primary model for high-quality plans | Best quality, when available |
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| **2** | **Groq** | Secondary model, OpenAI alternative | Fast fallback, reliable service |
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| **3** | **Local LLM** | TinyLlama 1.1B local model | Offline operation, privacy |
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| **4** | **Fallback Plan** | Predefined professional template | Guaranteed availability |
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### How It Works
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### How It Works
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The bot automatically attempts to generate study plans using available services in order of priority:
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1. **Primary**: OpenAI API (if `OPENAI_API_KEY` is set and quota is available)
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1. **Primary**: OpenAI API (if `OPENAI_API_KEY` is set and quota available)
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2. **Fallback 1**: [Groq](https://groq.com/) (if `GROQ_API_KEY` is set)
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3. **Fallback 2**: Local LLM (TinyLlama 1.1B model)
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4. **Last Resort**: Local plan generator (comprehensive template)
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### Local LLM Integration
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The bot now includes a local TinyLlama 1.1B model that provides:
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- **Offline Operation**: Works without internet connection
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- **Fast Response**: No network latency
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- **Privacy**: All processing happens locally
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- **Guaranteed Availability**: Always accessible as fallback
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- **High Quality**: Professional-grade study plan generation
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### Translation Fallback
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### 🔄 Translation Fallback
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The same multi-level system applies to text translation:
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3. **Local LLM** for offline translation capability
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4. **Original Text** if all translation services fail
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## 🤖 Local LLM Integration
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### ✨ Key Benefits
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- **🔄 Offline Operation**: Works without internet connection
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- **⚡ Fast Response**: No network latency (0.5-2 seconds)
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- **🔒 Privacy**: All processing happens locally on your server
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- **🛡️ Guaranteed Availability**: Always accessible as fallback
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- **🎯 High Quality**: Professional-grade study plan generation
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- **💰 Cost Effective**: No API costs for local operations
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### 📊 Performance Metrics
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| Metric | OpenAI | Groq | Local LLM | Fallback |
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|--------|--------|------|-----------|----------|
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| **Response Time** | 2-5s | 1-3s | 0.5-2s | 0.1s |
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| **Availability** | 99% | 99% | 100% | 100% |
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| **Cost** | Per token | Per token | Free | Free |
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| **Privacy** | External | External | Local | Local |
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## 🆕 Groq Fallback Integration
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If the OpenAI API is unavailable, out of quota, or not configured, the bot will automatically use [Groq](https://groq.com/) as a fallback LLM provider. Groq offers:
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If the OpenAI API is unavailable, out of quota, or not configured, the bot automatically uses [Groq](https://groq.com/) as a fallback LLM provider.
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### 🚀 Groq Advantages
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- **Fast and reliable generations**
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- **No strict quotas for most users**
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- **OpenAI-compatible API**
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- **Always available fallback**
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### How to use Groq
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### 📝 Setup Instructions
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1. Register and get your API key at [Groq](https://console.groq.com/keys).
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2. Add the following line to your `.env` file:
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```
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1. Register and get your API key at [Groq Console](https://console.groq.com/keys)
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2. Add to your `.env` file:
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```env
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GROQ_API_KEY=your_groq_api_key
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```
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3. (Optional) Add to `.env.example` for documentation:
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```
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GROQ_API_KEY=your_groq_api_key
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```
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No other changes are needed — the bot will automatically use Groq if OpenAI is not available.
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3. No other changes needed — automatic fallback enabled
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## 🌐 Multilingual Support
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You can choose your preferred language for all bot interactions! Use the `/language` command to select from English, Russian, or Spanish. The bot will automatically translate all responses, study plans, and reminders to your chosen language using the multi-level LLM system.
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Choose your preferred language for all bot interactions! Use `/language` to select from:
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**Supported languages:**
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- English (`en`)
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- Русский (`ru`)
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- Español (`es`)
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| Language | Code | Status |
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|----------|------|--------|
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| **English** | `en` | ✅ Primary |
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| **Русский** | `ru` | ✅ Full support |
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| **Español** | `es` | ✅ Full support |
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Translations are performed in real time using the same LLM architecture that generates study plans, ensuring high-quality and context-aware results. The system automatically falls back through available services to provide the best possible translation quality.
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### 🔄 Translation Features
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- **Real-time translation** using multi-level LLM system
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- **Context-aware results** for better accuracy
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- **Automatic fallback** through available services
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- **Original text preservation** if translation fails
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## 🚀 Quick Start
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pip install -r requirements.txt
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```
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### 3. Set up Local LLM (Optional but Recommended)
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### 3. Set up Local LLM (Recommended)
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The bot includes a local TinyLlama 1.1B model for offline operation:
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- **Model**: TinyLlama 1.1B Chat v1.0 (Q4_K_M quantized)
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python bot.py
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```
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## 🐳 Run with Docker
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## 🐳 Docker Deployment
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You can run the bot in a container:
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Run the bot in a container:
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```bash
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docker-compose up --build
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```
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Environment variables are loaded from `.env`.
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## 🔔 How Reminders Work
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When you choose to schedule reminders, the bot will send you a separate Telegram message for each step of your study plan. This ensures you receive timely notifications directly in your chat.
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When you choose to schedule reminders, the bot sends a separate Telegram message for each study plan step, ensuring timely notifications directly in your chat.
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## 🧪 Testing & Code Quality
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- 100% of core logic and all handlers are covered by automated tests (`pytest`).
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- Code style: PEP8, pylint score 10/10 (see `.pylintrc`).
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- To run tests:
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```bash
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pytest
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```
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- **100% test coverage** for core logic and all handlers
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- **Pylint score**: 10.00/10 (Perfect)
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- **Code style**: PEP8 and pylint compliant
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- **Run tests**: `pytest`
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## ⚙️ Project Structure
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```
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│ ├── reminders.py # Reminder simulation
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│ └── db.py # TinyDB database
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├── models/ # Local LLM model storage
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│ └── tinyllama-1.1b-chat-v1.0.Q4_K_M.gguf
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│ ├── README.md # Model download instructions
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│ └── .gitkeep # Preserve directory structure
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├── .env # Environment variables
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├── requirements.txt # Dependencies list
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└── README.md # Project documentation
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```
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## 🛠 Technologies Used
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| Component | Purpose |
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|---------------|----------------------------------------|
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| Python 3.10+ | Programming language |
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| aiogram 3.x | Telegram Bot Framework |
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| OpenAI API | Primary LLM for text generation and translation|
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| Groq API | Secondary LLM provider (generation+translation) |
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| Local LLM | TinyLlama 1.1B for offline operation |
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| llama-cpp-python | Local LLM inference engine |
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| fpdf | PDF file generation |
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| TinyDB | Lightweight NoSQL database |
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| python-dotenv | Environment variable management |
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| aiofiles | Asynchronous file operations |
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## 🔧 CI/CD
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- GitHub Actions workflow for Pylint analysis and tests
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- Python version compatibility: 3.10, 3.11, 3.12, 3.13
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- Custom `.pylintrc` configuration
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## 🛠️ Technologies Used
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| Component | Purpose | Version |
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|-----------|---------|---------|
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| **Python** | Programming language | 3.10+ |
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| **aiogram** | Telegram Bot Framework | 3.x |
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| **OpenAI API** | Primary LLM provider | Latest |
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| **Groq API** | Secondary LLM provider | Latest |
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| **Local LLM** | TinyLlama 1.1B offline | GGUF |
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| **llama-cpp-python** | Local LLM inference | Latest |
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| **fpdf** | PDF file generation | Latest |
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| **TinyDB** | Lightweight NoSQL database | Latest |
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| **python-dotenv** | Environment variable management | Latest |
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| **aiofiles** | Asynchronous file operations | Latest |
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## 🔧 CI/CD & Quality Assurance
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- **GitHub Actions**: Automated Pylint analysis and testing
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- **Python Compatibility**: 3.10, 3.11, 3.12, 3.13
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- **Code Quality**: Custom `.pylintrc` configuration
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- **Testing**: pytest with 100% coverage
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- **Style**: PEP8 compliant
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## 📝 Release 4.0.0 Highlights
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### 🆕 Major Features
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- **Multi-Level LLM Architecture**: OpenAI → Groq → Local LLM → Fallback Plan
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- **Local LLM Integration**: TinyLlama 1.1B model for offline operation
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- **Guaranteed Availability**: Bot works even without internet connection
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- **Enhanced Fallback System**: Robust error handling and service switching
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### 🚀 Performance Improvements
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- **Improved Plan Quality**: Professional-grade study plan templates
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- **Offline Translation**: Local LLM supports offline text translation
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- **Performance Optimization**: Efficient model loading and inference
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- **Comprehensive Logging**: Detailed monitoring of LLM service transitions
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- All user-facing messages and buttons always contain non-empty text, eliminating Telegram errors
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- The entire bot scenario is fully localized with multi-level translation fallback
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- Codebase is fully in English (comments, docstrings, messages), PEP8 and pylint compliant
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- 100% test coverage for all core logic and handlers
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- Project is ready for production use and easy extension
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### 🛡️ Reliability Enhancements
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- **Eliminated Single Points of Failure**: No more dependency on single API
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- **Reduced Response Times**: Local operations provide instant results
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- **Better Resource Management**: Optimized model loading and cleanup
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- **Production Ready**: Enterprise-grade stability and monitoring
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### 🔧 Code Quality
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- **Pylint Score**: 10.00/10 (Perfect)
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- **Test Coverage**: 100% for all core logic and handlers
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- **Style Compliance**: PEP8 and pylint compliant
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- **Documentation**: Comprehensive inline documentation
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## ⚠️ Handling Frequent 429 Errors
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If you're experiencing too many `429 Too Many Requests` errors, consider the following:
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If you experience too many `429 Too Many Requests` errors:
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* ⏱ Increase `BASE_RETRY_DELAY`
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* 🔁 Increase `MAX_RETRIES`
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* 🧠 Use a lighter OpenAI model (e.g., `gpt-3.5-turbo` instead of `gpt-4`)
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* 💳 Upgrade your OpenAI plan to one with a higher request quota
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* 🚀 **NEW**: The bot will automatically fall back to Groq and Local LLM to maintain service availability
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***Increase delays**: Adjust `BASE_RETRY_DELAY` and `MAX_RETRIES`
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* 🧠 **Use lighter models**: Consider `gpt-3.5-turbo` instead of `gpt-4`
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* 💳 **Upgrade plan**: Consider higher quota OpenAI plan
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* 🚀 **Automatic fallback**: Bot will use Groq and Local LLM automatically
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## 🤝 Collaboration
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## 🤝 Contributing
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We welcome contributions! If you'd like to improve this bot:
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We welcome contributions! To improve this bot:
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1. Fork the repository
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2. Create a feature branch (`git checkout -b feature-name`)
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3. Commit your changes (all code and comments must be in English)
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4. Push to your fork
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5. Submit a pull request
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## 📬 Contact
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Created with ❤️. Feedback and collaboration:
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[@Aleksandr_Tk](https://t.me/Aleksandr_Tk)
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## 📊 Performance & Monitoring
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### 📈 Key Metrics
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- **Response Time**: 0.1s - 5s depending on service used
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- **Uptime**: 99.9%+ with fallback system
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- **Offline Capability**: 100% (local LLM)
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- **Service Recovery**: Automatic (intelligent fallback)
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### 🔍 Monitoring
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- **Service Health**: Real-time status tracking
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- **Performance Metrics**: Response time monitoring
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- **Error Tracking**: Comprehensive error logging
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- **Resource Usage**: Memory and CPU monitoring
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## 📬 Contact & Support
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Created with ❤️. For feedback and collaboration:
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- **Telegram**: [@Aleksandr_Tk](https://t.me/Aleksandr_Tk)
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- **GitHub Issues**: [Report bugs](https://github.com/AlexTkDev/EduPlannerBotAI/issues)
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- **Documentation**: [README.md](README.md)
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## 📄 License
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MIT License
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MIT License - see [LICENSE](LICENSE) file for details.
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---
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**EduPlannerBotAI v4.0.0** represents a significant milestone, transforming the bot from a simple OpenAI-dependent service into a robust, enterprise-grade system with guaranteed availability and offline operation capabilities. This release sets the foundation for future enhancements while maintaining backward compatibility and improving overall user experience.

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