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    <title>Ayanda Phaketsi - Portfolio Projects</title>
    <link>https://phaketsi.vercel.app</link>
    <description>Latest projects from Ayanda Phaketsi, a Computer Science student at UCT specializing in full-stack development and AI.</description>
    <language>en-us</language>
    <lastBuildDate>Sat, 17 Oct 2026 00:16:27 GMT</lastBuildDate>
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    <copyright>Copyright 2026 Ayanda Phaketsi</copyright>
    <managingEditor>ayandaphaketsi@gmail.com (Ayanda Phaketsi)</managingEditor>
    <webMaster>ayandaphaketsi@gmail.com (Ayanda Phaketsi)</webMaster>
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      <title>Ayanda Phaketsi - Portfolio</title>
      <link>https://phaketsi.vercel.app</link>
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    <item>
      <title><![CDATA[MemGallery]]></title>
      <link>https://phaketsi.vercel.app/projects/memgallery</link>
      <guid isPermaLink="true">https://phaketsi.vercel.app/projects/memgallery</guid>
      <description><![CDATA[MemGallery is an AI-powered memory assistant Android app that democratizes brand-exclusive features like OPPO's Mind Space and Nothing's Essential Space, bringing automatic screenshot detection, multimodal capture, and semantic search to any Android 7.0+ device. Built with Jetpack Compose, Kotlin Coroutines, Hilt DI, Room, and Google's Gemini 2.5 Flash API, it automatically captures and processes screenshots, photos, audio, and text—extracting actionable insights (events, todos, reminders) and making everything searchable through natural language. The project showcases modern Android architecture (MVVM + Repository pattern),]]></description>
      <content:encoded><![CDATA[
        <h2>MemGallery</h2>
        <img src="https://res.cloudinary.com/dc3ko6fsn/image/upload/v1763763545/portfolio/gb1s7qvrp2onvkk5imlr.png" alt="MemGallery" style="max-width: 100%; height: auto;" />
        <p>MemGallery is an AI-powered memory assistant Android app that democratizes brand-exclusive features like OPPO's Mind Space and Nothing's Essential Space, bringing automatic screenshot detection, multimodal capture, and semantic search to any Android 7.0+ device. Built with Jetpack Compose, Kotlin Coroutines, Hilt DI, Room, and Google's Gemini 2.5 Flash API, it automatically captures and processes screenshots, photos, audio, and text—extracting actionable insights (events, todos, reminders) and making everything searchable through natural language. The project showcases modern Android architecture (MVVM + Repository pattern),</p>
        <p><strong>Technology:</strong> Kotlin</p>
        <p><strong>Tags:</strong> Kotlin, Android, Jetpack Compose, Material Design 3, MVVM, Clean Architecture, Hilt, Dagger, Room Database, Coroutines, Flow, WorkManager, Gemini API, Generative AI, Google AI SDK, Background Processing, Mobile Development, Open Source</p>
        <p><a href="https://github.com/Past-da-king/MemGallery/releases" target="_blank">View Live Project</a></p>
        <p><a href="https://github.com/Past-da-king/MemGallery" target="_blank">View Source Code</a></p>
      ]]></content:encoded>
      <dc:creator><![CDATA[Ayanda Phaketsi]]></dc:creator>
      <pubDate>Fri, 21 Nov 2025 04:36:02 GMT</pubDate>
      <category><![CDATA[Kotlin]]></category>
      <category><![CDATA[Android]]></category>
      <category><![CDATA[Jetpack Compose]]></category>
      <category><![CDATA[Material Design 3]]></category>
      <category><![CDATA[MVVM]]></category>
      <category><![CDATA[Clean Architecture]]></category>
      <category><![CDATA[Hilt]]></category>
      <category><![CDATA[Dagger]]></category>
      <category><![CDATA[Room Database]]></category>
      <category><![CDATA[Coroutines]]></category>
      <category><![CDATA[Flow]]></category>
      <category><![CDATA[WorkManager]]></category>
      <category><![CDATA[Gemini API]]></category>
      <category><![CDATA[Generative AI]]></category>
      <category><![CDATA[Google AI SDK]]></category>
      <category><![CDATA[Background Processing]]></category>
      <category><![CDATA[Mobile Development]]></category>
      <category><![CDATA[Open Source]]></category>
    </item>
    <item>
      <title><![CDATA[ayanda]]></title>
      <link>https://phaketsi.vercel.app/projects/ayanda</link>
      <guid isPermaLink="true">https://phaketsi.vercel.app/projects/ayanda</guid>
      <description><![CDATA[AIDA (AI-Driven Assistant) is a full-stack personal command center built with Next.js 15, MongoDB, and the Google Gemini API. It unifies task management, goal tracking, notes, and calendar events into a single dashboard. The core feature is an intelligent assistant that processes natural language commands (text and audio/multimodal) to execute CRUD operations, leveraging persistent user context and custom data models for dynamic goal calculation.]]></description>
      <content:encoded><![CDATA[
        <h2>ayanda</h2>
        <img src="https://res.cloudinary.com/dc3ko6fsn/image/upload/v1781036915/portfolio/t3tk3pkda76xo3tgklur.png" alt="ayanda" style="max-width: 100%; height: auto;" />
        <p>AIDA (AI-Driven Assistant) is a full-stack personal command center built with Next.js 15, MongoDB, and the Google Gemini API. It unifies task management, goal tracking, notes, and calendar events into a single dashboard. The core feature is an intelligent assistant that processes natural language commands (text and audio/multimodal) to execute CRUD operations, leveraging persistent user context and custom data models for dynamic goal calculation.</p>
        <p><strong>Technology:</strong> TypeScript</p>
        <p><strong>Tags:</strong> Next.js 15, React 19, TypeScript, MongoDB, Mongoose, NextAuth.js, Google Gemini API, AI/NLP, Tailwind CSS, shadcn/ui, Custom Theming, Multimodal Input, CRUD API</p>
        <p><a href="https://ayanda-flame.vercel.app/" target="_blank">View Live Project</a></p>
        <p><a href="https://github.com/Past-da-king/ayanda" target="_blank">View Source Code</a></p>
      ]]></content:encoded>
      <dc:creator><![CDATA[Ayanda Phaketsi]]></dc:creator>
      <pubDate>Wed, 29 Oct 2025 16:31:14 GMT</pubDate>
      <category><![CDATA[Next.js 15]]></category>
      <category><![CDATA[React 19]]></category>
      <category><![CDATA[TypeScript]]></category>
      <category><![CDATA[MongoDB]]></category>
      <category><![CDATA[Mongoose]]></category>
      <category><![CDATA[NextAuth.js]]></category>
      <category><![CDATA[Google Gemini API]]></category>
      <category><![CDATA[AI/NLP]]></category>
      <category><![CDATA[Tailwind CSS]]></category>
      <category><![CDATA[shadcn/ui]]></category>
      <category><![CDATA[Custom Theming]]></category>
      <category><![CDATA[Multimodal Input]]></category>
      <category><![CDATA[CRUD API]]></category>
    </item>
    <item>
      <title><![CDATA[StudyInc-startup]]></title>
      <link>https://phaketsi.vercel.app/projects/studyinc-startup</link>
      <guid isPermaLink="true">https://phaketsi.vercel.app/projects/studyinc-startup</guid>
      <description><![CDATA[StudyInc is a comprehensive Electron desktop application that transforms collaborative learning. It  integrates Pomodoro timers, real-time video calls, and task management within structured study sprints, enabling users to boost focus and productivity. Leveraging Next.js, Node.js, MongoDB, and Socket.IO, StudyInc provides a seamless, interactive environment for group study, complete with detailed analytics to track progress and optimize learning strategies.]]></description>
      <content:encoded><![CDATA[
        <h2>StudyInc-startup</h2>
        
        <p>StudyInc is a comprehensive Electron desktop application that transforms collaborative learning. It  integrates Pomodoro timers, real-time video calls, and task management within structured study sprints, enabling users to boost focus and productivity. Leveraging Next.js, Node.js, MongoDB, and Socket.IO, StudyInc provides a seamless, interactive environment for group study, complete with detailed analytics to track progress and optimize learning strategies.</p>
        <p><strong>Technology:</strong> TypeScript</p>
        <p><strong>Tags:</strong> ✦ JavaScript, TypeScript, Node.js, Next.js, React, Express.js, Electron, MongoDB, Socket.IO, WebRTC, Tailwind   CSS, Collaborative Study, Pomodoro Timer, Video Calls, Real-time Chat, Task Management, Analytics Dashboard, User Authentication, Sprint Management, Desktop Application, IPC, Notifications, REST API, JWT, Mongoose, Simple Peer, PeerJS, React Query, Radix UI, shadcn/ui</p>
        
        <p><a href="https://github.com/playza5388/StudyInc-startup" target="_blank">View Source Code</a></p>
      ]]></content:encoded>
      <dc:creator><![CDATA[Ayanda Phaketsi]]></dc:creator>
      <pubDate>Sun, 05 Oct 2025 23:52:47 GMT</pubDate>
      <category><![CDATA[✦ JavaScript]]></category>
      <category><![CDATA[TypeScript]]></category>
      <category><![CDATA[Node.js]]></category>
      <category><![CDATA[Next.js]]></category>
      <category><![CDATA[React]]></category>
      <category><![CDATA[Express.js]]></category>
      <category><![CDATA[Electron]]></category>
      <category><![CDATA[MongoDB]]></category>
      <category><![CDATA[Socket.IO]]></category>
      <category><![CDATA[WebRTC]]></category>
      <category><![CDATA[Tailwind   CSS]]></category>
      <category><![CDATA[Collaborative Study]]></category>
      <category><![CDATA[Pomodoro Timer]]></category>
      <category><![CDATA[Video Calls]]></category>
      <category><![CDATA[Real-time Chat]]></category>
      <category><![CDATA[Task Management]]></category>
      <category><![CDATA[Analytics Dashboard]]></category>
      <category><![CDATA[User Authentication]]></category>
      <category><![CDATA[Sprint Management]]></category>
      <category><![CDATA[Desktop Application]]></category>
      <category><![CDATA[IPC]]></category>
      <category><![CDATA[Notifications]]></category>
      <category><![CDATA[REST API]]></category>
      <category><![CDATA[JWT]]></category>
      <category><![CDATA[Mongoose]]></category>
      <category><![CDATA[Simple Peer]]></category>
      <category><![CDATA[PeerJS]]></category>
      <category><![CDATA[React Query]]></category>
      <category><![CDATA[Radix UI]]></category>
      <category><![CDATA[shadcn/ui]]></category>
    </item>
    <item>
      <title><![CDATA[notebook]]></title>
      <link>https://phaketsi.vercel.app/projects/notebook</link>
      <guid isPermaLink="true">https://phaketsi.vercel.app/projects/notebook</guid>
      <description><![CDATA[An AI-powered web application built with React and TypeScript that converts static PDF files into interactive, editable study notebooks using the Google Gemini API. It features real-time Markdown streaming, intelligent content summarization, on-demand content expansion, searching, and custom quiz generation based on saved material, all managed client-side using local storage.]]></description>
      <content:encoded><![CDATA[
        <h2>notebook</h2>
        
        <p>An AI-powered web application built with React and TypeScript that converts static PDF files into interactive, editable study notebooks using the Google Gemini API. It features real-time Markdown streaming, intelligent content summarization, on-demand content expansion, searching, and custom quiz generation based on saved material, all managed client-side using local storage.</p>
        <p><strong>Technology:</strong> TypeScript</p>
        <p><strong>Tags:</strong> React, TypeScript, Google Gemini API, AI, PDF Processing, Markdown, Vite, Tailwind CSS, Client-Side Storage, Streaming, Quiz Generation, Highlight.js</p>
        <p><a href="https://notebook-beige-six.vercel.app/" target="_blank">View Live Project</a></p>
        <p><a href="https://github.com/Past-da-king/notebook" target="_blank">View Source Code</a></p>
      ]]></content:encoded>
      <dc:creator><![CDATA[Ayanda Phaketsi]]></dc:creator>
      <pubDate>Sun, 05 Oct 2025 22:07:52 GMT</pubDate>
      <category><![CDATA[React]]></category>
      <category><![CDATA[TypeScript]]></category>
      <category><![CDATA[Google Gemini API]]></category>
      <category><![CDATA[AI]]></category>
      <category><![CDATA[PDF Processing]]></category>
      <category><![CDATA[Markdown]]></category>
      <category><![CDATA[Vite]]></category>
      <category><![CDATA[Tailwind CSS]]></category>
      <category><![CDATA[Client-Side Storage]]></category>
      <category><![CDATA[Streaming]]></category>
      <category><![CDATA[Quiz Generation]]></category>
      <category><![CDATA[Highlight.js]]></category>
    </item>
    <item>
      <title><![CDATA[rl]]></title>
      <link>https://phaketsi.vercel.app/projects/rl</link>
      <guid isPermaLink="true">https://phaketsi.vercel.app/projects/rl</guid>
      <description><![CDATA[A Q-learning implementation to solve package collection tasks in the classic Four-Rooms grid world environment. The agent learns optimal policies across three complexity levels: single-package collection, multi-package unordered collection, and strict sequential multi-package collection (RGB order), supporting both deterministic and stochastic environment dynamics.]]></description>
      <content:encoded><![CDATA[
        <h2>rl</h2>
        
        <p>A Q-learning implementation to solve package collection tasks in the classic Four-Rooms grid world environment. The agent learns optimal policies across three complexity levels: single-package collection, multi-package unordered collection, and strict sequential multi-package collection (RGB order), supporting both deterministic and stochastic environment dynamics.</p>
        <p><strong>Technology:</strong> Python</p>
        <p><strong>Tags:</strong> Python, Reinforcement Learning, Q-Learning, Grid World, NumPy, Matplotlib, Machine Learning</p>
        <p><a href="https://github.com/Past-da-king/rl" target="_blank">View Live Project</a></p>
        <p><a href="https://github.com/Past-da-king/rl" target="_blank">View Source Code</a></p>
      ]]></content:encoded>
      <dc:creator><![CDATA[Ayanda Phaketsi]]></dc:creator>
      <pubDate>Fri, 03 Oct 2025 22:09:37 GMT</pubDate>
      <category><![CDATA[Python]]></category>
      <category><![CDATA[Reinforcement Learning]]></category>
      <category><![CDATA[Q-Learning]]></category>
      <category><![CDATA[Grid World]]></category>
      <category><![CDATA[NumPy]]></category>
      <category><![CDATA[Matplotlib]]></category>
      <category><![CDATA[Machine Learning]]></category>
    </item>
    <item>
      <title><![CDATA[lead-generation]]></title>
      <link>https://phaketsi.vercel.app/projects/lead-generation</link>
      <guid isPermaLink="true">https://phaketsi.vercel.app/projects/lead-generation</guid>
      <description><![CDATA[A high-performance B2B lead generation engine built on FastAPI and Google Gemini (GenAI SDK). It uses a two-step streaming AI pipeline (research and formatting) with tools (Google Search, URL Context) to create deeply analyzed, structured sales profiles and hyper-personalized outreach messages in real-time, streamed via Server-Sent Events (SSE) to a dynamic frontend UI.]]></description>
      <content:encoded><![CDATA[
        <h2>lead-generation</h2>
        
        <p>A high-performance B2B lead generation engine built on FastAPI and Google Gemini (GenAI SDK). It uses a two-step streaming AI pipeline (research and formatting) with tools (Google Search, URL Context) to create deeply analyzed, structured sales profiles and hyper-personalized outreach messages in real-time, streamed via Server-Sent Events (SSE) to a dynamic frontend UI.</p>
        <p><strong>Technology:</strong> HTML</p>
        <p><strong>Tags:</strong> FastAPI, Python, Google Gemini, GenAI SDK, Prompt Engineering, Server-Sent Events (SSE), Streaming, AI, Lead Generation, Pydantic, Jinja2, CSV, REST API, Tailwind CSS, HTML</p>
        <p><a href="https://github.com/Past-da-king/lead-generation" target="_blank">View Live Project</a></p>
        <p><a href="https://github.com/Past-da-king/lead-generation" target="_blank">View Source Code</a></p>
      ]]></content:encoded>
      <dc:creator><![CDATA[Ayanda Phaketsi]]></dc:creator>
      <pubDate>Fri, 03 Oct 2025 21:56:48 GMT</pubDate>
      <category><![CDATA[FastAPI]]></category>
      <category><![CDATA[Python]]></category>
      <category><![CDATA[Google Gemini]]></category>
      <category><![CDATA[GenAI SDK]]></category>
      <category><![CDATA[Prompt Engineering]]></category>
      <category><![CDATA[Server-Sent Events (SSE)]]></category>
      <category><![CDATA[Streaming]]></category>
      <category><![CDATA[AI]]></category>
      <category><![CDATA[Lead Generation]]></category>
      <category><![CDATA[Pydantic]]></category>
      <category><![CDATA[Jinja2]]></category>
      <category><![CDATA[CSV]]></category>
      <category><![CDATA[REST API]]></category>
      <category><![CDATA[Tailwind CSS]]></category>
      <category><![CDATA[HTML]]></category>
    </item>
    <item>
      <title><![CDATA[portfolio]]></title>
      <link>https://phaketsi.vercel.app/projects/portfolio</link>
      <guid isPermaLink="true">https://phaketsi.vercel.app/projects/portfolio</guid>
      <description><![CDATA[A sophisticated, self-updating portfolio platform built on Next.js and TypeScript, featuring a secure administration dashboard that integrates the Google Generative AI (Gemini) API to automatically fetch code from GitHub repositories, analyze the codebase, and generate detailed, professional Markdown project descriptions for MongoDB storage.]]></description>
      <content:encoded><![CDATA[
        <h2>portfolio</h2>
        
        <p>A sophisticated, self-updating portfolio platform built on Next.js and TypeScript, featuring a secure administration dashboard that integrates the Google Generative AI (Gemini) API to automatically fetch code from GitHub repositories, analyze the codebase, and generate detailed, professional Markdown project descriptions for MongoDB storage.</p>
        <p><strong>Technology:</strong> TypeScript</p>
        <p><strong>Tags:</strong> Next.js, React, TypeScript, Tailwind CSS, NextAuth, MongoDB, Mongoose, Gemini API, AI Integration, Full-Stack, typescript</p>
        <p><a href="https://github.com/Past-da-king/portfolio" target="_blank">View Live Project</a></p>
        <p><a href="https://github.com/Past-da-king/portfolio" target="_blank">View Source Code</a></p>
      ]]></content:encoded>
      <dc:creator><![CDATA[Ayanda Phaketsi]]></dc:creator>
      <pubDate>Fri, 03 Oct 2025 15:57:14 GMT</pubDate>
      <category><![CDATA[Next.js]]></category>
      <category><![CDATA[React]]></category>
      <category><![CDATA[TypeScript]]></category>
      <category><![CDATA[Tailwind CSS]]></category>
      <category><![CDATA[NextAuth]]></category>
      <category><![CDATA[MongoDB]]></category>
      <category><![CDATA[Mongoose]]></category>
      <category><![CDATA[Gemini API]]></category>
      <category><![CDATA[AI Integration]]></category>
      <category><![CDATA[Full-Stack]]></category>
      <category><![CDATA[typescript]]></category>
    </item>
    <item>
      <title><![CDATA[rednexa]]></title>
      <link>https://phaketsi.vercel.app/projects/rednexa</link>
      <guid isPermaLink="true">https://phaketsi.vercel.app/projects/rednexa</guid>
      <description><![CDATA[Nexa is a capstone project that addresses the critical issue of limited internet access in rural and
  township communities by providing a decentralized, offline-first mobile communication platform. Leveraging
  Delay-Tolerant Networking (DTN) principles, Nexa enables secure, end-to-end encrypted messaging, group
  chats, and multimedia sharing through device-to-device "message hopping" via Bluetooth and Wi-Fi Direct,
  ensuring communication resilience even without traditional internet infrastructure. This innovative approach
   empowers underserved populations with reliable connectivity, fostering digital inclusion and community
  engagement]]></description>
      <content:encoded><![CDATA[
        <h2>rednexa</h2>
        
        <p>Nexa is a capstone project that addresses the critical issue of limited internet access in rural and
  township communities by providing a decentralized, offline-first mobile communication platform. Leveraging
  Delay-Tolerant Networking (DTN) principles, Nexa enables secure, end-to-end encrypted messaging, group
  chats, and multimedia sharing through device-to-device "message hopping" via Bluetooth and Wi-Fi Direct,
  ensuring communication resilience even without traditional internet infrastructure. This innovative approach
   empowers underserved populations with reliable connectivity, fostering digital inclusion and community
  engagement</p>
        <p><strong>Technology:</strong> Kotlin</p>
        <p><strong>Tags:</strong> ✦ DTN, Android, Kotlin, Jetpack Compose, P2P, Offline-First, Cryptography, Google Tink, Nearby Connections   API, Mobile Development</p>
        
        <p><a href="https://github.com/Past-da-king/rednexa" target="_blank">View Source Code</a></p>
      ]]></content:encoded>
      <dc:creator><![CDATA[Ayanda Phaketsi]]></dc:creator>
      <pubDate>Fri, 03 Oct 2025 04:41:55 GMT</pubDate>
      <category><![CDATA[✦ DTN]]></category>
      <category><![CDATA[Android]]></category>
      <category><![CDATA[Kotlin]]></category>
      <category><![CDATA[Jetpack Compose]]></category>
      <category><![CDATA[P2P]]></category>
      <category><![CDATA[Offline-First]]></category>
      <category><![CDATA[Cryptography]]></category>
      <category><![CDATA[Google Tink]]></category>
      <category><![CDATA[Nearby Connections   API]]></category>
      <category><![CDATA[Mobile Development]]></category>
    </item>
    <item>
      <title><![CDATA[mcp3]]></title>
      <link>https://phaketsi.vercel.app/projects/mcp3</link>
      <guid isPermaLink="true">https://phaketsi.vercel.app/projects/mcp3</guid>
      <description><![CDATA[Calculon is a real-time, conversational math chatbot powered by Google Gemini and a decoupled Modular Calculation Protocol (MCP) server. The system utilizes FastAPI and WebSockets to enable secure, streamed tool use, forcing the AI to delegate all arithmetic operations (add, subtract, multiply, divide) to a precise, dedicated backend service. The frontend displays the AI's thoughts, tool calls, and results in real time, showcasing advanced RAG/Tool-Use orchestration.]]></description>
      <content:encoded><![CDATA[
        <h2>mcp3</h2>
        
        <p>Calculon is a real-time, conversational math chatbot powered by Google Gemini and a decoupled Modular Calculation Protocol (MCP) server. The system utilizes FastAPI and WebSockets to enable secure, streamed tool use, forcing the AI to delegate all arithmetic operations (add, subtract, multiply, divide) to a precise, dedicated backend service. The frontend displays the AI's thoughts, tool calls, and results in real time, showcasing advanced RAG/Tool-Use orchestration.</p>
        <p><strong>Technology:</strong> Python</p>
        <p><strong>Tags:</strong> Python, FastAPI, WebSockets, Google Gemini, Generative AI, Tool Use, Modular Calculation Protocol (MCP), Vanilla JavaScript, HTML, CSS, Real-time Streaming, Asynchronous Programming, Uvicorn, python</p>
        <p><a href="https://github.com/Past-da-king/mcp3" target="_blank">View Live Project</a></p>
        <p><a href="https://github.com/Past-da-king/mcp3" target="_blank">View Source Code</a></p>
      ]]></content:encoded>
      <dc:creator><![CDATA[Ayanda Phaketsi]]></dc:creator>
      <pubDate>Fri, 03 Oct 2025 01:10:06 GMT</pubDate>
      <category><![CDATA[Python]]></category>
      <category><![CDATA[FastAPI]]></category>
      <category><![CDATA[WebSockets]]></category>
      <category><![CDATA[Google Gemini]]></category>
      <category><![CDATA[Generative AI]]></category>
      <category><![CDATA[Tool Use]]></category>
      <category><![CDATA[Modular Calculation Protocol (MCP)]]></category>
      <category><![CDATA[Vanilla JavaScript]]></category>
      <category><![CDATA[HTML]]></category>
      <category><![CDATA[CSS]]></category>
      <category><![CDATA[Real-time Streaming]]></category>
      <category><![CDATA[Asynchronous Programming]]></category>
      <category><![CDATA[Uvicorn]]></category>
      <category><![CDATA[python]]></category>
    </item>
    <item>
      <title><![CDATA[clia]]></title>
      <link>https://phaketsi.vercel.app/projects/clia</link>
      <guid isPermaLink="true">https://phaketsi.vercel.app/projects/clia</guid>
      <description><![CDATA[clia is an advanced, conversational AI assistant for software engineering, implemented as a command-line tool (CLI) and a web UI. Powered by the Google Gemini model, it uses a local Model Context Protocol (MCP) tool server to safely and transparently interact with the user's filesystem and command line. It features streaming AI thoughts, mandatory tool call permissions, and precise file manipulation capabilities, enabling developers to refactor, debug, and implement features through natural language commands.]]></description>
      <content:encoded><![CDATA[
        <h2>clia</h2>
        <img src="https://res.cloudinary.com/dc3ko6fsn/image/upload/v1781038463/portfolio/ewytcfk9vhpiuntra5mc.png" alt="clia" style="max-width: 100%; height: auto;" />
        <p>clia is an advanced, conversational AI assistant for software engineering, implemented as a command-line tool (CLI) and a web UI. Powered by the Google Gemini model, it uses a local Model Context Protocol (MCP) tool server to safely and transparently interact with the user's filesystem and command line. It features streaming AI thoughts, mandatory tool call permissions, and precise file manipulation capabilities, enabling developers to refactor, debug, and implement features through natural language commands.</p>
        <p><strong>Technology:</strong> Python</p>
        <p><strong>Tags:</strong> Python, Google Gemini, GenAI, LLM, Tool Use, MCP, rich, prompt-toolkit, FastAPI, CLI, Software Engineering, Asynchronous Programming, python</p>
        <p><a href="https://pypi.org/project/clia-swe-ai/" target="_blank">View Live Project</a></p>
        <p><a href="https://github.com/Past-da-king/clia" target="_blank">View Source Code</a></p>
      ]]></content:encoded>
      <dc:creator><![CDATA[Ayanda Phaketsi]]></dc:creator>
      <pubDate>Fri, 03 Oct 2025 01:02:41 GMT</pubDate>
      <category><![CDATA[Python]]></category>
      <category><![CDATA[Google Gemini]]></category>
      <category><![CDATA[GenAI]]></category>
      <category><![CDATA[LLM]]></category>
      <category><![CDATA[Tool Use]]></category>
      <category><![CDATA[MCP]]></category>
      <category><![CDATA[rich]]></category>
      <category><![CDATA[prompt-toolkit]]></category>
      <category><![CDATA[FastAPI]]></category>
      <category><![CDATA[CLI]]></category>
      <category><![CDATA[Software Engineering]]></category>
      <category><![CDATA[Asynchronous Programming]]></category>
      <category><![CDATA[python]]></category>
    </item>
    <item>
      <title><![CDATA[verilookie]]></title>
      <link>https://phaketsi.vercel.app/projects/verilookie</link>
      <guid isPermaLink="true">https://phaketsi.vercel.app/projects/verilookie</guid>
      <description><![CDATA[Verilookie is a full-stack web application that provides unified deepfake and AI-generated media detection, utilizing a Python FastAPI backend and a React frontend. It uniquely integrates a gamified learning system powered by the Google Gemini API to offer personalized, adaptive quizzes, educating users while protecting them from misinformation.]]></description>
      <content:encoded><![CDATA[
        <h2>verilookie</h2>
        
        <p>Verilookie is a full-stack web application that provides unified deepfake and AI-generated media detection, utilizing a Python FastAPI backend and a React frontend. It uniquely integrates a gamified learning system powered by the Google Gemini API to offer personalized, adaptive quizzes, educating users while protecting them from misinformation.</p>
        <p><strong>Technology:</strong> Python</p>
        <p><strong>Tags:</strong> Python, FastAPI, React, JavaScript, Deep Learning, Vision Transformer (ViT), Hugging Face, NVIDIA AI, Google Gemini, Docker, Gamification, Cybersecurity, python</p>
        <p><a href="https://github.com/Maphuti-Shilabje/verilookie" target="_blank">View Live Project</a></p>
        <p><a href="https://github.com/Maphuti-Shilabje/verilookie" target="_blank">View Source Code</a></p>
      ]]></content:encoded>
      <dc:creator><![CDATA[Ayanda Phaketsi]]></dc:creator>
      <pubDate>Fri, 03 Oct 2025 00:54:06 GMT</pubDate>
      <category><![CDATA[Python]]></category>
      <category><![CDATA[FastAPI]]></category>
      <category><![CDATA[React]]></category>
      <category><![CDATA[JavaScript]]></category>
      <category><![CDATA[Deep Learning]]></category>
      <category><![CDATA[Vision Transformer (ViT)]]></category>
      <category><![CDATA[Hugging Face]]></category>
      <category><![CDATA[NVIDIA AI]]></category>
      <category><![CDATA[Google Gemini]]></category>
      <category><![CDATA[Docker]]></category>
      <category><![CDATA[Gamification]]></category>
      <category><![CDATA[Cybersecurity]]></category>
      <category><![CDATA[python]]></category>
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