🤖 AI Shopping + Mood Chatbot using Rasa, Python & Telegram From Concept to Deployment – NLP | Telegram Bot | Intelligent Assistant

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🤖 Hi, I'm Jorie The Bot

Made with ❤️ by Shaif Khan

Hello Connections! 👋 I'm Shaif Khan, and I’m thrilled to introduce one of my most exciting AI-powered creations — a multi-functional chatbot built using Rasa Framework and Python, integrated with Telegram to assist users in:

🛍 Choosing the right smartphones/laptops 📰 Staying updated with the latest tech news 🧘‍♂️ Interacting emotionally through a Mood Bot feature

This project merges Conversational AI, natural language understanding (NLU), and Telegram integration — all deployed from a local setup using Ngrok. It's a full-stack chatbot that showcases the future of interactive AI assistants.

💻 Tech Stack & Tools:

      🔹 Rasa (NLU + Core) – For intent classification and dialogue management
      
      🔹 Python – Backend logic and custom actions
      
      🔹 HTML, CSS, JavaScript – Frontend interaction for web interface
      
      🔹 Ngrok – Secure tunnel to expose local Rasa server to Telegram
      
      🔹 Telegram Bot API – For real-time chatbot communication
      
      🔹 📦 Libraries: TensorFlow, ujson, requests, and more
      
      🔹 ⚙️ Dev Tools: Anaconda, C++ Build Tools, virtual environments

🧠 Core Chatbot Capabilities:

      🗣️ NLP-powered Intent Recognition via trained stories and utterances
      
      🛒 Product Recommendation: Suggests phones/laptops based on user needs
      
      📰 Tech News Fetcher: Responds with trending news snippets
      
      😇 Mood Bot: Replies empathetically to emotional cues
      
      💬 Telegram Integration: Works inside the Telegram app in real time
      
      🌐 Frontend-Friendly: Optional UI with HTML + JS for web interaction

🛠️ Development Highlights:

      ✅ Custom NLU pipelines for better accuracy
      
      ✅ Fallback & error-handling policies for smooth conversations
      
      ✅ Telegram connector with live updates via Ngrok
      
      ✅ Lightweight & modular project structure
      
      ✅ Fully offline-ready using Anaconda environments

💡 Why This Project Stands Out: Whether you're diving into Conversational AI, exploring Rasa, or building real-time Telegram bots, this project offers a complete blueprint — from intent design to deployment — that’s both scalable and user-friendly.

It’s a blend of AI, backend engineering, and chatbot UX, and perfect for anyone interested in real-world NLP projects.

🔗 Want a Demo or the Code? 📁 GitHub Repository: 👉 Click to View Project on GitHub

📌 Tags & Topics #RasaFramework #Chatbot #PythonProjects #TelegramBot #NLP #AIProjects #TechNewsBot #MoodBot #Ngrok #TensorFlow #Anaconda #FullStackAI #ConversationAI #Python #MachineLearning

🧭 Visual Workflow Diagram – AI Chatbot Architecture

User (Telegram App) ⬇️ Telegram Bot API
⬇️ Ngrok Tunnel (Port Forwarding) ⬇️ Rasa Server (NLU + Core) ⬇️ Rasa Action Server (Python Logic) ⬇️ Response Generation 🔄 ⬇️ Telegram (User receives reply)