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desc: "A Retrieval-Augmented Generation (RAG) chatbot built with Streamlit, ChromaDB, and LLMs for dynamic Q&A.",
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subdesc:
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"This RAG chatbot enables document ingestion (PDF, TXT, DOCX, CSV, JSON), manual text entry, and URL scraping to build a persistent knowledge base in ChromaDB. It integrates configurable LLMs via the Groq API and Sentence-Transformers embeddings to deliver concise, context-aware answers, with optional Google Custom Search augmentation for time-sensitive queries. Conversations are stored in SQLite, and new facts are heuristically extracted and learned automatically.",
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href: "https://github.com/sa-fw-an/RAG-ChatBot",
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texture: "./textures/project/rag-chatbot.mov",
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logo: "./assets/project/chatbot-logo.svg",
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logoStyle: {
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backgroundColor: "#0B1624",
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border: "0.2px solid #1A2433",
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boxShadow: "0px 0px 60px 0px #2248704D",
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},
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spotlight: "./assets/spotlight2.png",
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tags: [
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{
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id: 1,
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name: "Streamlit",
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path: "./assets/coding/streamlit.svg",
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},
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{
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id: 2,
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name: "Python",
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path: "./assets/coding/python.svg",
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},
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{
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id: 3,
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name: "SQLite",
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path: "./assets/coding/sql.svg",
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},
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{
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id: 4,
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name: "HTML",
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path: "./assets/coding/html.svg",
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},
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{
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id: 5,
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name: "CSS",
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path: "./assets/coding/css.svg",
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},
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],
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},
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{
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title: "Blockchain Voting System",
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desc: "A secure and transparent voting system built on blockchain technology, ensuring integrity and privacy in the electoral process.",
@@ -145,7 +103,116 @@ export const myProjects = [
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},
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],
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},
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{
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{
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title: "RAG-ChatBot",
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desc: "A Retrieval-Augmented Generation (RAG) chatbot built with Streamlit, ChromaDB, and LLMs for dynamic Q&A.",
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subdesc:
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"This RAG chatbot enables document ingestion (PDF, TXT, DOCX, CSV, JSON), manual text entry, and URL scraping to build a persistent knowledge base in ChromaDB. It integrates configurable LLMs via the Groq API and Sentence-Transformers embeddings to deliver concise, context-aware answers, with optional Google Custom Search augmentation for time-sensitive queries. Conversations are stored in SQLite, and new facts are heuristically extracted and learned automatically.",
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href: "https://github.com/sa-fw-an/RAG-ChatBot",
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texture: "./textures/project/rag-chatbot.mov",
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logo: "./assets/project/chatbot-logo.svg",
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logoStyle: {
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backgroundColor: "#0B1624",
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border: "0.2px solid #1A2433",
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boxShadow: "0px 0px 60px 0px #2248704D",
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},
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spotlight: "./assets/spotlight2.png",
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tags: [
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{
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id: 1,
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name: "Streamlit",
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path: "./assets/coding/streamlit.svg",
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},
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{
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id: 2,
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name: "Python",
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path: "./assets/coding/python.svg",
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},
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{
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id: 3,
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name: "SQLite",
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path: "./assets/coding/sql.svg",
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},
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{
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id: 4,
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name: "HTML",
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path: "./assets/coding/html.svg",
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},
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{
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id: 5,
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name: "CSS",
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path: "./assets/coding/css.svg",
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},
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],
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},
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{
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title: "AI Chat Application",
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desc: "A sophisticated ChatGPT-like interface with advanced file processing, multiple AI model support, and comprehensive user management built with Next.js 15 and React 19.",
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subdesc:
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"This AI-powered chat application delivers a complete ChatGPT experience with enhanced capabilities including multi-format file processing (PDFs, images, documents), intelligent document analysis with GPT-4 Vision, and advanced memory systems using vector embeddings. Features include real-time streaming responses, mobile-responsive design with ARIA accessibility compliance, context-aware conversations, and seamless integration with OpenAI's latest models. The application supports PDF text extraction, image analysis, document Q&A, and maintains conversation context across sessions with persistent storage.",
desc: "A powerful Markdown parser built with modern web technologies, enabling seamless conversion of Markdown for live editing and previewing with download options.",
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