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<p>Knative is a Kubernetes-based platform to deploy and manage serverless workloads. Eventing is a key feature for Serverless Computing. They deliver their information to a specified target to make a whole system interactive. The problem is that every kind of event cannot be treated as the same one in the Knative ecosystem because the shape of each event depends on its sources. Knative Eventing is designed to be consistent with the CloudEvents definition to keep interoperability. To make this happen, the Knative Eventing community already has several kinds of event type definitions such as GitHub, AWS S3, GCP Pub/Sub, etc.<br> This project aims to add two event types:</p> <ul> <li>an event source that is able to generate CloudEvents when a new container image is uploaded to Docker Hub.</li> <li>another event source that is able to generate CloudEvents on success/failure of Task/Pipeline and every step of a Pipeline created by Tekton CI/CD.</li> </ul> <p>Both components would help application developers focus on developing applications itself and make Serverless Computing more diverse.</p>

I will be developing DashBot - the AI assistant for API Dash which supercharges developer productivity by helping developers automate tedious tasks, follow best practices, interact & obtain contextual suggestions, all via natural-language input. DashBot will be designed in a modular and extensible manner and provide the following list of features: 1. Explain responses & identify any discrepancy 2. Debug requests based on Status codes & Error messages 3. Generate API documentation 4. Understand API and generate tests 5. Generate plots & visualizations for API responses along with ability to customize 6. Generate API integration frontend code for frontend frameworks like React, Flutter, etc. For each of the tasks benchmark evaluations will also be done so that it is easier for end users to choose the right backend LLM. Add support for various API Authentication Methods such as, Basic authentication, API Auth, API key, Bearer token, JWT Bearer, Digest Auth, OAuth 1.0, OAuth 2.0.

<p>Music Blocks is a free and open-source, browser-based software, designed basically for students to learn music in fun and interactive way. To get started with “music blocks”, newbies need to have a fundamental understanding of the software, what are the things can be done and importantly how things can be done. To address this requirement, “music block” has a user guide. But the existing user guide lacks most of the important information about the software components, how each building blocks in the software can be related to music and especially some examples of how to create music with the software. The objective of this project is to create a user manual which would be a simple and comprehensive guide while providing samples and related explanations. Deliverables of the project will be as follows:</p> <ul> <li>Improve the Music blocks user guide content to be easily approachable to newbies. </li> <li>Implement a documentation website for Music Blocks user guide. </li> <li>Prepare a downloadable version of the Music Blocks user manual in Portable Document Format(PDF).</li> <li>Make the website expandable for online contributions to documentation from the website itself.</li> </ul>

Variant filtration is key to rare disease discovery. For a rare disease discovery app to be successful, it must be able to cleanly represent the relevant variants in a patient’s genome. Phenopackets present a method of filtering genes based on a patient’s phenotype. Phenotype data can narrow down the set of at risk genes clinicians need to parse during rare disease discovery using tools like exomiser. This project will use phenopackets to dynamically filter variants for the purpose of rare disease discovery. This project has two deliverables, each with their own set of requirements: A method to filter genes using phenopacket data. Must be optimized for speed, given this is a dynamic application. However, speed will be limited by the FHIR Genomics Operations reference implementation response time. A clean, easily understandable presentation of variants useful for manual review. Two views should be provided: one for the most at risk variants, and another for a more detailed view of each variant in at risk genes. The former should have a graphical component. The latter does not need to have as clean of a presentation. Users should be able to identify the most at risk variants within 5-10 seconds of the page loading.

The "Musical Ideation through Generative AI" project aims to integrate a Language Learning Model (LLM) with Sugar Labs' MusicBlocks platform, enabling users to compose and enhance musical compositions. It will start with implementing an efficient ABC parser for MusicBlocks, ensuring robust extraction of musical information from ABC notation. Next, the project will tune and benchmark the LLM to generate high-quality musical compositions in ABC format. Once tuned, the LLM will be deployed to a server environment, and API endpoints will be set up to enable interaction with MusicBlocks. Users will initiate compositions in MusicBlocks, which will be sent to the LLM for enhancement. The LLM will generate multiple compositions based on the user's input, which will be converted back to MusicBlocks format for further enhancement. Throughout the project, integration testing and flow testing will ensure seamless interaction between MusicBlocks and the LLM API. Comprehensive documentation will provide insights into the implementation process, results of benchmarking and testing, and recommendations for future improvements. This integration of AI-generated compositions into MusicBlocks aims to inspire creativity, deepen musical understanding, and enhance the learning experience for users

The GA4GH Service Info API is a required component across standards such as TES, WES, and TRS, providing essential metadata about a service. Currently, each implementation must manually develop and maintain its own /service-info endpoint, leading to duplication, inconsistent metadata, and difficulty in supporting new capabilities such as security and extensibility features. This project proposes a reusable GA4GH ServiceInfo Sidecar a lightweight proxy service that runs alongside existing GA4GH services and handles /service-info requests centrally, while forwarding all other requests transparently to the backend. The sidecar will generate standard-compliant responses using a combination of static configuration (config.yaml) and dynamic metadata collected through a plugin system, enabling seamless support for service-specific and custom extensions without modifying backend code. The project will deliver a production-ready implementation with schema validation, extensibility aligned with GA4GH specifications, and deployment support via Docker and Kubernetes. Additionally, the sidecar will support Trusted Execution Environments (TEE) by advertising attestation capabilities via the ServiceInfo API and delivering attestation reports through a dedicated endpoint, enabling verifiable trust without implementing low-level attestation logic.

Thousands of bioinformatics workflows registered on public platforms like Dockstore and WorkflowHub cannot run on modern cloud platforms. Not because the science is wrong, but because the engineering hasn't caught up. Missing containers, hardcoded paths, HPC-specific executors, and unstructured inputs and outputs make these workflows incompatible with GA4GH's WES standard and cloud-based research platforms. Workflow Clinic fixes this automatically. It is a Python-based CLI tool with two core components. The Workflow Critic scans a workflow repository, runs a deterministic rule engine followed by an optional AI agent team, and produces a structured diagnosis.json report identifying every cloudification gap with severity levels and remediation suggestions. The Workflow Doctor reads this report, applies fixes directly to the workflow files using a 3-layer strategy (AST-based, regex-based, and AI-assisted as a last resort), and opens Pull Requests to propose the changes. GitHub interaction is purely optional examine and fix work fully offline without any credentials. When a GitHub PAT is provided, the tool can additionally publish findings as GitHub issues and open Pull Requests. Without a PAT, the same outputs are generated locally as issue.md and fix.md files.

<p>Sugarizer Deployment Tool is a tool for Sugarizer. He is for deploying Sugarizer on multiple device a keep it updated. Make the installation and updated easy for the user.</p> <p>Sugarizer is a way to use Sugar on any device using web technologies. Sugarizer can be deployed on many devices including Android phones and tablets. The goal of this specific project is to create the "Sugarizer Deployment and Management Tool for Android".</p> <p><strong>Expected results</strong></p> <p>Sugarizer Server Deployment and Management Tool is a GUI Tool working on GNU/Linux, Mac and Windows to deploy and configure Android devices using ADB (Android Debug Bridge).</p> <ul> <li>Inventory : Collect and store devices data like serial number, os version, device name, installed applications, current Android launcher and Sugarizer availability.</li> <li>Application Manager : Install or remove applications using APK files.</li> <li>File Manager : Add / Remove files</li> <li>Input Manager : Click / Touch coordinates on the screen, launch applications to perform automations.</li> <li>Scenario Writer : Allow non developpers to create sequences to perform all the steps previously defined.</li> </ul>

The Music Blocks v4 project is a complete overhaul of the original Music Blocks project, which was derived from the Turtle Blocks project. The existing implementation, which started in 2015 using native Vanilla JavaScript, lacks modern front-end tooling and ecosystem standards, leading to difficulties in maintenance and subpar performance. The v4 project uses improved application architecture, modern tools (such as Vite, ESLint, Prettier, Docker, Jest, Cypress, etc.), better languages (TypeScript and Sass), and libraries (React for UI rendering). This will significantly enhance the overall developer and user experience, maintainability, and performance. The proposal focuses on implementing one of the main features of Music Blocks, the "Project Builder", which is currently missing in the new version (v4). The Project Builder is a graphical blocks manager module used to create Music Blocks programs, including interactive blocks like Start, Rhythm, Note, Pitch, Instrument, and many more. These blocks can be dragged, dropped, and clicked to perform actions or open context menus. By implementing the Project Builder feature end-to-end, users will be able to create different musical patterns seamlessly. This will bring the v4 project on par with the capabilities of the old version (v1) and provide a more accessible, efficient, and user-friendly application for users to create music through an interactive web application.

The Music Blocks v4 project is a complete overhaul of the original Music Blocks project, which was derived from the Turtle Blocks project. The existing implementation, which started in 2015 using native Vanilla JavaScript, lacks modern front-end tooling and ecosystem standards, leading to difficulties in maintenance and subpar performance. The v4 project uses improved application architecture, modern tools (such as Vite, ESLint, Prettier, Docker, Jest, Cypress, etc.), better languages (TypeScript and Sass), and libraries (React for UI rendering). This will significantly enhance the overall developer and user experience, maintainability, and performance. The proposal focuses on implementing one of the main features of Music Blocks, the "Masonry Framework" (previously code-builder/project-builder), which is currently missing in the new version (v4). The is a graphical blocks manager module used to create Music Blocks programs, including interactive blocks like Start, Rhythm, Note, Pitch, Instrument, and many more. These blocks can be dragged, dropped, and clicked to perform actions or open context menus. By implementing the Masonry feature end-to-end, users will be able to create different musical patterns seamlessly. This will bring the v4 project on par with the capabilities of the old version (v3) and provide a more accessible, efficient, and user-friendly application for users to create music through an interactive web application.

The Sugarizer Human Activity Pack project aims to enhance the educational tools provided by Sugar Labs by developing two engaging and interactive activities. The first, the 3D Human Body Activity, will expand on the existing anatomical visualization tool by integrating multiple 3D models, including skeletal, human body and organ system. It will allow users to toggle between different layers, interact with body structures dynamically, and engage in real-time collaborative learning. Additional features such as interactive quizzes, UI/UX refinements, and localization support will ensure accessibility and usability across different regions and devices. The second component, the Stickman Animation Activity, will introduce an interactive keyframe animation tool where users can manipulate a stick figure by adjusting its nodes to create animations. This tool will support essential animation features such as playback, speed control, and exporting animations as videos. It will also include a collection of pre-designed templates for common movements like running, jumping, and dancing. A standout feature of this activity is the ability to import a photo of a human body and generate a corresponding stick figure in the same pose using AI-assisted pose detection. By the end of the project, Sugar Labs will gain two fully functional, optimized, and localized activities that provide immersive learning experiences in human anatomy and animation principles. The enhancements to the 3D Human Body Activity will enable students to explore anatomy in a more interactive and engaging way, moving beyond static textbook images to dynamic 3D models. The Stickman Animation Activity will encourage creativity and spatial understanding by allowing students to experiment with motion and animation concepts. Together, these activities will significantly contribute to making education more engaging, interactive, and widely accessible.

<p>Building a project which uses ScanCode as a library in a web and REST API application that allows you to scan code on demand by entering a URL and then store the scan results. Travis or Github integration to scan on commit with webhooks. Including the feature to scan based on a received tweet of similar IRC or IM integration.</p>

<p>The SIMPLE Grid project is an extension of the SIMPLE Framework that combines popular configuration management technologies such as Puppet/Ansible and container orchestration technologies such as Docker Swarm/Kubernetes to allow deployment of complex computing clusters using a single site level configuration file. The proposed project aims to improve functionality, correctness, and efficiency of different stages of SIMPLE Grid Framework.</p>

<p>Signal intelligence describes the gathering of information out of intercepted radio signals with unknown origin and unknown parameters. GNU Radio has already the ability to do signal intelligence, but it is only possible through some detours. Real-time signal intelligence is hardly possible. The tool <code>gqrx</code> has some of this ability (real-time AM/FM demodulation), but there is no final solution for this problem at this time. The target of this project is to develop an easily accessible and extendible solution for this workflow including automatic signal detection and automatic modulation classification. Further deliverables are a radio service allocation database, blind synchronization methods and an automatic demodulation block.</p>

<p>The aim of this project is to re-implement Warp with Fibers to demonstrate the effectiveness of Fibers. To complete that, the following goals need to be reached:</p> <ol> <li>Implement non-blocking I/O support for Fibers.</li> <li>Recognize the parts of code related with I/O and threads, and rewrite them with Fibers</li> <li>Write a benchmark for the performance of Warp.</li> <li>Perform a detailed analysis and tune performance.</li> </ol>

<p>During the GSoC I'm going to complete the following tasks:</p> <ol> <li>Enhance the suggestions sorting algorithm using the ML-way inspired by <a href="https://open.afterthedeadline.com/about/technology-overview" target="_blank">after the deadline</a>'s (section "The Spelling Corrector")</li> <li>Migrate the server-side of the LanguageTool to the modern lightweight framework</li> <li>Migrate the LanguageTool from Maven to Gradle</li> </ol>

<p>The goal of this project is to enhance the currently present SUSI AI bots, create a chatbot of SUSI AI for Twitch and create a web bot plugin for SUSI AI by creating required APIs for storage and processing of it in SUSI server and creating the bot builder wizard on SUSI skills page. A web bot plugin is a chatbot for the website of a user which would replace the traditional contact form. Users would be able to fully customise their SUSI AI chatbots by adding custom replies to messages of their clients which will be backed up by SUSI skills. The customisation includes but is not limited to designing the theme of bot and configuring the bot by enabling/disabling default SUSI skills.</p>

<p>This project completes the leftover bits of GSoC'17 and adds a new Rack middleware - Server Timing Middleware</p>

<p>The goal of the project is to create some code for International Components for Unicode (ICU) Librariary that compute dates in Tibetan calendar and also to create a new locale and add some metadata to Unicode Common Locale Data Repository(CLDR) to ensure that CLDR can represent the Tibetan calendars and dates.</p> <p>During the course of the project our primary focus was on two widespread types of Tibetan calendar calculations, Phugpa and Tsurphu.</p>

<p>In Robotics, it is crucial to identify humans and efficiently distinguish them. This gives the ability to perform further challenging tasks such as personalized interactions, social navigation and surveillance. Currently, Robocomp only uses face recognition for human identification. The aim of this project is to integrate other modalities, such as rgb image, skeleton-based pose and silhouette of the body. Using these modalities various human identification components, namely gait recognition and person re-identification, will be integrated into Robocomp</p>

<p>Humans and robots coexist together in today's world and to make these interactions more meaningful, one of the capacities that a robot must certainly perform is to understand the people it is interacting with human beings, and sometimes the knowledge of how many people the robot needs to interact with becomes crucial information. The aim of this project is to add upon the existing functionalities of the ‘People Counter’ in the ‘Human Detection Component’ allowing a more enriched interaction between robots and humans. This will allow the robot to make better decisions based on the density of people present in the area.</p>

<p>Swarm robotics is an approach to the coordination of large numbers of robots in order to tackle a given task inspired by the observation of social animals and their behaviour, making individuals tasks to resolve group problems. My proposal to this idea is to implement examples of collective behaviors using swarm robotics strategies in new or old scenarios of the RoboComp RCIS simulator, like collective exploration of the scenario, patterns formation, morphogenesis or another collective activities. Also, there would be a verbal or non-verbal communication between the swarm components in order to send some commands to the crowd.</p>

<p>The aim of this project is to integrate social behaviors into the RoboComp navigation agent. Mobile robots that encounter people on a regular basis must react to them in some way or the other. Traditional robot control algorithms for path planning and obstacle avoidance treat all sensor readings identically, as foreign objects that must be avoided. However, for a mobile robot that operates around people, these traditional algorithms may not follow the social norms. Even simple conventions like move to the right when a person is encountered might not be honored by these algorithms. However, people would want to, or rather tend to perceive robots-particularly assistive robots, as human like. So catering to this need social behavior will be implemented via certain cost functions.</p>