AI Wellness Companion is an AI-powered mental health support platform designed to promote emotional well-being and self-care. The application offers a safe and empathetic space where users can share their thoughts and feelings, while receiving AI-driven responses tailored to their emotional state. The system integrates: Conversational AI for empathetic mental health support. Mood tracking and journaling to help users monitor emotional patterns. Personalized coping strategies based on user input and preferences. Voice interaction for a more natural and accessible experience. Secure frontend (React) for smooth user experience. Robust backend (Python) to handle AI logic, APIs, and data processing. This project aims to bridge technology with mental wellness, making mental health support more accessible, private, and available anytime.

Code Compass – AI-Powered Open-Source Contribution Helper Code Compass makes open-source contribution easier by helping developers understand complex codebases, visualize dependencies, and find actionable contribution opportunities. Core Problem New developers struggle with large, unfamiliar repositories and lack clear starting points. Code Compass bridges this gap with AI-driven insights and interactive visualization. Key Features ✅ AI-Powered Analysis – GPT-5-based repository summarization, code explanations, and intelligent Q&A. ✅ Visual Knowledge Graphs – Interactive dependency maps using NetworkX + PyVis for files, classes, and functions. ✅ Smart Contribution Guidance – Detects TODOs, missing tests, and suggests beginner-friendly GitHub issues. ✅ Multi-Language Support – Handles Python, JavaScript, TypeScript, HTML, CSS, and config files. How It Works Repo Ingestion – Clone any GitHub repo via API. Graph Mapping – Build a knowledge graph of imports, function calls, and file relationships. AI Insight Layer – GPT-5 answers natural language questions, explains architecture, and recommends contributions. Interactive Exploration – Filter graphs, view file summaries, and discover improvement areas. Tech Stack Frontend: Streamlit, PyVis Backend: FastAPI, Python AI & NLP: GPT-5 (via AIML), Google Generative AI embeddings, FAISS for semantic search Visualization: NetworkX, Plotly Integration: GitHub API (PyGithub) Why It’s Innovative Unlike basic code search tools, Code Compass combines graph visualization, AI-driven explanations, and predictive contribution detection. It not only answers “what” and “where” but also explains “why” and “how”, empowering newcomers to contribute confidently. One-Line Summary: Code Compass transforms codebases into interactive, explainable maps, making open-source projects accessible to everyone.

The e-commerce platform (https://ecommerce-lyart-five-31.vercel.app/) is a sophisticated web application designed to deliver a seamless and innovative shopping experience. Developed using Next.js for server-side rendering, React for dynamic UI, and Tailwind CSS for responsive styling, it is backed by a Neon PostgreSQL database for robust data management. The platform integrates Groq AI to power advanced features, including: Voice Search: Users can search products using voice input, processed via Groq’s Whisper model to extract keywords (e.g., "laptop" from "search for laptops"), with a 4MB file size limit for audio uploads. Image Search: Allows product searches by uploading images, enhancing accessibility. Product Filters: Enables users to refine searches by category, price, and rating. Smart Filters: AI-driven filtering for personalized results based on user behavior. Responsive Design: Ensures compatibility across devices, from mobile to desktop.

ORION: AI-Driven Space Operations Automation is an AI-powered system that enhances space mission safety, efficiency, and automation. It processes real-time telemetry data using Kafka, detects anomalies with an Autoencoder model, predicts failures with an LSTM-based predictive maintenance system, and enables autonomous decision-making using Reinforcement Learning (PPO). ORION's Streamlit dashboard provides real-time mission insights, minimizing human errors and optimizing spacecraft operations. Additionally, AutoGen multi-agent AI enhances decision-making and automation. This solution reduces operational costs, improves mission reliability, and scales for satellite fleet management, interplanetary missions, and deep-space exploration. ORION is designed for space agencies, aerospace companies, and research institutions, ensuring mission success and sustainability.

The Smart Network Infrastructure Planner builds on the findings of the PASQAL Hackathon on Quantum Computing, which revealed the significant risks that climate change poses to telecommunications infrastructure, with disruptions expected to escalate in underserved regions by 2047. Using these insights, the planner integrates AI, quantum computing, and dynamic datasets to optimize telecommunications deployment, focusing on climate resilience and improving connectivity in vulnerable communities. Key innovations envisioned for the planner include: Dynamic AI-Driven Analysis: Predicts vulnerabilities and recommends climate-resilient strategies, enhancing operational efficiency, reducing downtime, and minimizing risk. Integration of Hugging Face Datasets: Provides real-time, adaptive planning by leveraging environmental and demographic data to identify and prioritize high-need areas. Interactive Streamlit Application: Empowers stakeholders to simulate deployment scenarios, visualize complex data, and collaborate effectively, fostering alignment and better decision-making. Budget Optimization: Prioritizes resource allocation for underserved regions, ensuring cost efficiency and maximizing ROI while addressing connectivity gaps. Sustainability Metrics: Embeds long-term resilience and environmental standards into planning to support sustainable development goals and enhance corporate social responsibility. These features deliver measurable business outcomes, including enhanced network reliability, optimized resource utilization, cost savings, and improved service in underserved regions. By addressing both current and future challenges, the planner empowers organizations to bridge the digital divide, mitigate climate risks, and unlock new opportunities in emerging markets. It transforms research findings from the PASQAL Hackathon into actionable strategies that support sustainable and equitable connectivity while creating competitive advantages in uncertain environments.

It is an innovative Streamlit-powered application designed to revolutionize document handling. It supports multi-format uploads, including PDFs, DOCX, PPTX, and XLSX, and leverages AI for advanced processing tasks like summarization, quiz generation, and content combination. The app provides an intuitive drag-and-drop interface, real-time insights through a responsive UI, and professional PDF export options. Key features include AI-powered summarization for concise content extraction, quiz generation in multiple formats (MCQs, True/False, etc.), and combining documents while maintaining structure and coherence. With a sleek, modern design enhanced by animations, the Smart Document Processor ensures a seamless user experience. It is built on cutting-edge technologies like Python libraries (ReportLab, Pandas) and Groq API for AI integration. This tool is perfect for use cases in hackathons, education, and corporate settings, automating tedious document tasks and saving valuable time. The app’s potential for real-time analytics and future enhancements like cloud integration make it a forward-thinking solution for document management. Whether you are a student, educator, or professional, the Smart Document Processor is tailored to empower you with intelligent automation and robust capabilities.

This AI-powered platform is designed to enhance English communication skills, with a focus on personalized feedback for writing and speaking improvement. The platform is ideal for students preparing for exams such as IELTS, PTE, and DET, as well as anyone looking to refine their English proficiency. Users can follow a 30-day structured writing plan, where they submit essays and receive in-depth feedback on areas like grammar, coherence, sentence structure, vocabulary usage, and writing style. For speaking practice, users can record their audio on various topics and receive real-time, AI-generated feedback on pronunciation, fluency, intonation, and word usage. The platform also transcribes audio submissions, allowing users to review their spoken content and identify areas for improvement. A key feature is the ability to track progress over time, with the platform maintaining previous conversations and interactions, providing continuity and enabling users to monitor their improvement journey. By offering both text and audio responses, this platform serves as a comprehensive tool to improve English communication skills, making it easier for students to gain confidence and fluency in both academic and professional settings.

EnglishCoach is an AI-powered app designed to improve writing and speaking skills for IELTS, PTE, and DET exams. It offers tailored 30-day, 45-day, and 60-day writing modules, focusing on grammar, coherence, and vocabulary, with real-time feedback. The speaking module provides instant pronunciation and fluency analysis through AI-driven conversation practice, helping users enhance their speaking skills in exam-like conditions. Personalized study plans and progress tracking ensure targeted improvements, making EnglishCoach a comprehensive tool for mastering English communication.By using data-driven insights, EnglishCoach tracks each student’s progress and adapts the lessons to their individual learning curve, ensuring continuous improvement and personalized support. With modules for writing and speaking, EnglishCoach is the ultimate tool for anyone aiming to excel in English communication exams and beyond.

This is a Quranic Knowledge AI Chatbot designed to provide answers directly from the Quran in Arabic, followed by translations and explanations in the same language as the user's input. The chatbot also provides detailed references, including Para, Surah, and Ayah numbers, for each answer. The model is specifically designed to answer queries related to the Quran. Key features include: -Quranic Verses in Arabic: Provides the relevant Quranic verse in Arabic for each query. -Language-Specific Explanations: Delivers explanations and translations in the user's input language. -Detailed References: Includes Para, Surah, and Ayah numbers for each Quranic reference. The process of the code involves utilizing a RAG (Retrieval-Augmented Generation) pipeline to ensure enhanced contextual accuracy. When a user inputs a query, the system retrieves relevant verses using Faiss for fast and scalable vector searches. The AI models, specifically IBM Granite and MiniLM, then generate accurate and contextually appropriate responses. The output is delivered through a Streamlit interface, which provides an interactive and user-friendly experience. Future enhancements include integrating Hadith and Sunnah, along with voice recognition capabilities.

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