Build RAG pipelines & AI agents with LangChain, automate workflows with n8n. Shipped a live medical AI chatbot on AWS.

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Md Danish Alam  • Peerlist

Live Website: https://heatwavefashion.sbs HeatWave Fashion is a responsive online shopping platform that blends style with technology. It features real-time weather updates to help users pick the perfect outfit, a secure login system (email & Google OAuth), and a smooth, mobile-friendly experience across devices. Key Highlights: - Trendy product showcase with new arrivals & top products - Shopping cart with easy add/remove and checkout options - Weather-based outfit recommendations powered by Open-Meteo & OpenStreetMap APIs - Secure authentication with JWT and Firebase OAuth Built using React.js, Tailwind CSS, Node.js, Express.js, MongoDB, this project demonstrates full-stack development and practical API integrations for real-world e-commerce applications.

HeatWave Fashion – Responsive E-commerce Stor

Developed an "AI-powered desktop assistant" with 95% speech recognition accuracy, capable of automating tasks like web searches, emails, WhatsApp messages, and app launches, reducing manual effort by 60%. Integrated OpenCV for face recognition and APIs (ChatGPT, Gemini, Google Speech, Wikipedia) for smart responses. Designed with a scalable architecture, making it expandable for NLP and smart home IoT integration.

JARVIS – AI Voice Assistant

Built a fully deployed, production-ready medical chatbot that answers health questions using Retrieval-Augmented Generation grounded entirely in the Gale Encyclopedia of Medicine, not the model's general knowledge.How it works: Medical PDFs are chunked (700 chars, 80 overlap) and embedded with BAAI/bge-small-en-v1.5, then indexed in Pinecone with MMR search for relevant, non-redundant retrieval. Groq's LLaMA 3.1 8B Instant generates answers strictly from retrieved context, bringing response time down from 60-90s on local Mistral/GGUF to 2-5s.Hallucination control: A 3-layer filtering pipeline (LLM medical-intent check, similarity threshold ≥ 0.75, and a refusal-phrase check) stops the bot from answering anything outside medicine. Tested against 35 non-medical questions spanning tech, geography, and general knowledge: 35/35 correctly refused. 15/15 medical questions answered accurately with verified page citations.Beyond the model, it's a full product: Google OAuth login with guest mode, PostgreSQL-backed session history, bookmarks, and persistent source citations, dark/light theme, text-to-speech playback, HTML chat export, and an in-app issue reporter. Containerized with Docker and served through Nginx with SSL on AWS EC2.Stack: Python, Flask, LangChain, Groq API, Pinecone, PostgreSQL, SQLAlchemy, Docker, AWS EC2, Nginx, Google OAuth 2.0🔗 Live: <a target="_blank" rel="noopener noreferrer nofollow ugc" class="break-all link-break text-gray-500 hover:underline" href="https://medencyclo.duckdns.org/">https://medencyclo.duckdns.org</a> 💻 Open-source: MIT licensed