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Backend projects covering pagination, caching, internationalization (i18n), and queuing systems in JavaScript. These projects focus on efficient data handling, performance optimization, multi-language support, and asynchronous task management for building scalable applications.
An advanced multimodal Retrieval Augmented Generation (RAG) system leveraging Gemini, HuggingFace embeddings, and Pinecone Vector DB to semantically parse complex PDF documents, with an asynchronous microservice architecture using Kafka, Langchain, FastAPI, JWT authentication, and Docker for scalable, real-time contextual knowledge extraction.
PyQt5 GUI controlling a background daemon that fetches messages from a server, processes them with a local AI via Ollama and Chroma, and sends back the response. Perfect for building automated, intelligent messaging flows.
CSV File Processor is a full-stack application for efficiently processing and managing CSV product data with real-time currency conversions. The application supports asynchronous processing of large datasets (200K+ rows), provides robust filtering and sorting capabilities, and uses Redis caching for optimized performance.