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This project aims to develop an intuitive Message Timestamp Date Picker for Rocket.Chat, replacing manual timestamp code entry with a user-friendly UI component. Currently, users must manually type complex codes like <t:1732557600>, which creates friction and is error-prone for non-technical users. I will solve this problem by implementing a comprehensive system with three layers: Core Utilities for timestamp conversion and validation, UI Components creating an intuitive modal with selection options and preview, and Integration Layer connecting to Rocket.Chat's existing systems. Deliverables include complete timestamp utility functions, TimestampPicker modal with intuitive inputs, message composer integration, rendering system for displaying formatted timestamps, comprehensive testing, and documentation. The solution will support all timestamp formats across platforms, significantly improving user experience when communicating time-based information.

My proposal focuses on enhancing the Rocket.Chat platform with an AI-driven feature, "AI Query Assistant," aimed at solving the challenge of efficiently handling user queries. Leveraging a Retrieval-Augmented Generation (RAG) pipeline, the assistant will accurately interpret and respond to user requests using AI-based image recognition. This integration will significantly streamline the process of request handling, reducing response time, and improving overall user satisfaction. The project involves configuring the RAG pipeline with advanced AI components, ensuring adaptability to different service domains, such as healthcare and IT support. Key deliverables include a fully integrated AI assistant within Rocket.Chat, capable of intelligent interaction, alongside comprehensive documentation for ease of use and future scalability. The successful implementation of this project will result in a more intuitive, efficient, and user-friendly query resolution mechanism within the Rocket.Chat environment.

<p>The project goal is to establish a test infrastructure which supports unit testing, UI testing and Integration testing. Unit tests and UI tests will be written for the android project to test the new features and code changes done in the project before getting merged in the main repository. The goal is to confirm that no new code gets merged unless it passes all the tests that will be run at build time i.e. the new code works as designed and does not cause any regression issues by breaking other functionality/tests. The test infrastructure will be designed in a way that it will tell the developer what method or function or Which piece of code is causing the error or tests to fail. So It will be easy to find which portion of code is causing an error and the developer can fix that. Proper test automation consists of the generation of test coverage reports as it helps in identifying the areas of missing test coverage. So the generation of test reports using Codecov is also an important goal of this project.</p>

This project proposes the Scheduled ZIM Generation feature for the Kiwix WP1 Selections interface. It introduces an automated system that allows users to schedule periodic regeneration of ZIM files from their selections (like SPARQL or WikiProject-based). Currently, users must manually trigger ZIM generation, which leads to outdated content for dynamic sources. The new system enables users to set a frequency (monthly or quarterly) and a maximum number of regenerations (with a max. like 4), along with email notifications. A scheduling mechanism will run in the backend, checking for due tasks, queuing ZIM generation jobs in zimfarm, sending notifications, and cleaning up old files to manage storage. Key components (deliverables): - A Vue.js UI for configuring schedules, viewing status, and managing tasks. Flask-based REST API endpoints for handling schedule data and triggering generation. - A scheduler to automate task execution. - Email notifications and cleanup logic for outdated ZIMs. - Full test coverage and documentation for both users and developers.

<p>The Rocket chat team has been sincerely working on improving the Android App by regularly adding great features and making them available to users through updates on the Google Play store. Play store is a great platform for making the app available to all users but there are countries where play services are banned/not available. Hence there is a great requirement for other app hosting platforms so that people of these countries can also use Rocket.Chat apps. This problem can be solved by using F-Droid. F-Droid is a community-maintained software repository for Android. Apps hosted on Fdroid can be installed from the F-Droid website or client app without the need to register. Being a catalog of Android FOSS applications. It is available in almost every country in the world. Rocket chat legacy android client is recently replaced by React Native and needs to be updated on F-Droid, Apart from this there are few other features like integrating Fastlane in the android module and use it to run the existing jobs and create a new job to upload the build to play console Other features include Improving CI workflow and create jobs to generate separate builds for both Fdroid and Play store.</p>

<p>Livechat is a package that adds the ability to embed a pop-up support chat to your website. For example when you want to interact with users visiting your website and help them with their problems, then this feature of RocketChat helps you with that. All you need to do embed a script on to your static website. Live chat agents who wield this tool use it to make customers happy and satisfied.</p> <p>This project adds real-time monitoring to livechat which will be an important feature as this will be helpful for livechat agents in the following way:-</p> <ul> <li><strong>More information about the user</strong>:- Track important information related to visitors, such as the <em>current page, location, time on site, local time</em>, etc, even though the visitor has not yet started a conversation with an agent.</li> <li><strong>Edit Info Panel for livechat with the user</strong>.</li> <li><strong>Increase Response TIme</strong>:- Agent will be able to start a conversation with a specific visitor directly from the list, improving the proactivity of the Live chat team.</li> <li><strong>New Admin Panel providing more info of users</strong></li> <li><strong>Add sentiment analysis on user messages</strong>:- When chat will be closed, sentiment analysis will be applied on user messages and shown on the admin dashboard for future use.</li> </ul>

This project builds a Gemini CLI extension that solves MCP's context bloat problem for Rocket.Chat developers. Current MCP servers expose an entire platform's API surface, meaning every agent session wastes tokens on hundreds of tool definitions the project will never use. The Minimal MCP Server Generator lets developers describe their use case in plain English and produces a production-ready MCP server covering only the endpoints they actually need. The generator goes beyond raw API wrappers by composing multi-step workflow tools: declarative step graphs that chain API calls, AI reasoning, conditional branching, and data transforms into single high-level operations. It supports two compilation targets: a standalone webhook + REST server that runs anywhere, and an Apps-Engine bridged mode for realtime event interception. The key deliverables include: a Gemini CLI extension with endpoint discovery, schema lookup, and project generation tools; a six-pass workflow validation pipeline that catches and self-corrects LLM mistakes before codegen; additive tool generation that adds new tools to existing servers without overwriting; protocol-level test generation via MCP Inspector; runtime hardening with endpoint allow-lists; and a PlatformProvider abstraction with a Mattermost dry-run proving the generator's portability beyond Rocket.Chat. This approach reduces token costs, fits within free-tier limits, and makes MCP-based Rocket.Chat development accessible to any workspace regardless of plan.

<p>MIPv6 is the base standard from the IETF for IP based mobility management in wireless networks. The next generation mobility management schemes are mainly following the protocol stack of MIPv6. Until today ns-3 – which aims to replace the aging ns2 and its associated old-featured simulators – does not have even in its latest version a MIPv6 module that is fully compliant to the IETF specification. To fill this gap, I am going to implement a novel MIPv6 simulation model which can be integrated into ns-3. The project idea aims at testing the code in different network scenarios, containing different link layer technologies such as Wi-Fi, WiMAX and LTE. The current implementation of LTE does not have support of IPv6 in ns-3. So, the idea of testing MIPv6 code into LTE would follow IPv6 support implementation in LTE first and then the MIPv6 support. So, ns-3 researchers can benefit themselves with the addition of this feature. Thus, implementation of MIPv6 in ns-3 as the base mobility management solution and providing LTE support within it could help the current network researchers working on ns-3.</p>

Checkstyle is widely used to detect code style violations, but many of its formatting-related issues are trivial and time-consuming to fix manually. This project aims to introduce an auto-fix module that can automatically correct formatting violations reported by specific Checks. The work involves evaluating existing auto-fix tools and libraries (e.g., OpenRewrite, CleanThat), selecting or building a reliable code modification engine, and designing an API for triggering code changes. A set of fixable formatting Checks will be selected, and their fix logic will be implemented in a maintainable way. The module will also include logic to prevent conflicting fixes and, if successful, may be proposed for integration into Checkstyle’s core to support plugin reuse.

<p>KIO framework is used by KDE applications to provide file management abilities. This framework provides almost all file management functions that one will ever need. However it doesn’t provide any support for file management as a privileged user. So whenever there is a need to perform file management tasks with escalated privileges the application simply shows an error. A casual user may not see it as a problem but for power users, sysadmins, developers this is a huge impedance. Many users get around this by starting the whole application as root. Running Qt/KDE GUI solves the issue but its a very dangerous solution. Dangerous because if not handled properly it can cause irreversible damage to the the system. To address this issue some KDE applications are disabling being executed as root. For example, the next versions of Dolphin and Kate will show an error message and exit when started with root privileges.</p> <p>Polkit is just the tool which can solve this problem. It is the standard framework used by Linux desktops to grant privileged actions to unprivileged processes. The goal of this project is to add Polkit support in KIO and further integrate it in dolphin.</p>

<p>FHIR (or Fast Healthcare Interoperability Resources) is a standard for exchanging electronic health records. It describes elements (called resources) and an API (or application programming interface) for implementation of the same. FHIR Narratives are human-readable representations of resources.</p> <p><strong>The project aims at adding support for FHIR Narratives to the FHIR2 Module of OpenMRS.</strong> Following are the overall objectives of the project:</p> <ul> <li>Create FHIR narratives for all resources defined by OpenMRS FHIR module.</li> <li>Develop a framework to support implementation-driven overrides for FHIR narratives.</li> <li>Add support for localization of the generated narratives.</li> </ul>

sktime in its current state does not support categorical variables in input data and this has been an often requested feature from its users. This project aims to add categorical support (for exogeneous input) to the forecasting and transformation modules by reworking the base framework layer and datatypes module. Another objective is to ensure categorical data works when used in sktime pipelines and relevant compositors.

<p>Currently, the coala Online module lacks support for all the bears. Bears with non-optional settings are ignored. The first goal of this project is to have a powerful online module that provides backend and frontend interface to be able to do code analysis with any given bear. The project focusses on enhancing coala-html by introducing results and bear search and filtering on basis of parameters. The next thing where the project will help us is that it will provide an effective bear search mechanism on coala.io and make projects.coala.io configurable and extensible.</p>

<p>OpenCV.js exposes JavaScript API of dnn module that allows web apps to do deep learning model inference in web browsers. This capability enables web developers to create intelligent usages, like image classification, object detection, segmentation and style transfer, with rich web contents, like images, videos and camera streams. Although OpenCV.js dnn module is using WebAssembly with multi-threading and SIMD128 optimization, there still exists a huge gap between OpenCV.js and OpenCV native. This is because OpenCV native can leverage more advanced hardware features and even ML-specific accelerators via native instructions and ML APIs. Web Neural Network API (WebNN) is an emerging web standard that allows web apps to access the AI hardware accelerations. It can get near-native performance on a variety of Intel-based platforms through the open source module oneDNN. Thus, in this proposal, I illustrate my idea about how to integrate WebNN into OpenCV.js and accelerate dnn module.</p>

<p>Sympy is currently supporting Stochastic Processes, Random matrices, Joint, Continuous, and Discrete distributions in its stats module. Compound Distributions introduced in 2018, does not provide complete support. Therefore, I plan to do the following during this summer.</p> <p>• Sampling from external libraries.</p> <p>• Adding and testing currently implemented Stochastic Processes.</p> <p>• Assumptions of dependence between Random Variables.</p> <p>• Improving and adding support for Compound Distributions.</p> <p>• Improving Joint Distributions Framework and adding more distributions.</p> <p>• Adding support for Mixture Distributions.</p>

<p>This project involves improving the existing ARVR Server by adding support for the premium Mobile VR platforms. The goal is to improve the existing GDNatives for GearVR and implement support for the Daydream devices. This can be done by improving the newly implemented VR backend of Godot. The "Native mobile" interface can be modified to support both GearVR and Daydream. Alternatively, the existing Oculus interface can also be modified to support GearVR and a new interface can be designed to introduce Daydream support.</p>

Federated Learning (FL) is a machine learning (ML) approach that allows models to be trained collaboratively and distributedly without sharing individual data points. WebGPU, a modern web standard and API, provides low-level, high-performance access to a device's GPU through web browsers. It aims to enable developers to create complex graphical applications and experiences on the web by utilizing modern GPU hardware for efficient graphics rendering. Due to their extensive usage and customized optimizations, current Federated Learning (FL) systems frequently concentrate on certain device types, such as smartphones or Internet of Things (IoT) devices. Nevertheless, FL's adaptability to other device kinds may be limited by this device-centric optimization, necessitating substantial coding and redesign work to modify FL systems for diverse device types. Because developers wind up building different and fragmented codebases for each device, this method violates software engineering principles of code reusability, making maintenance more difficult and impeding the effective deployment of FL. In this proposal, a novel WebGPU based federated learning network for heterogeneous device network is proposed. The proposal aims to deliver a working federated learning system supported by web browsers along with additional features.

<p>Panda3D is a mature 3D rendering engine both in age and functionality, addressing the need for the rapid prototyping of games while still providing stability for large projects. As a result of this maturity, however, Panda has been slow to take advantage of newer platforms and devices, with no support for iOS and only experimental support for Android. Adding support for iOS will make the engine much more appealing to new developers, while also creating the opportunity to update more antiquated areas of the engine. Many of these features will aid in future work on Android support as well.</p> <p>Goals for this project include:</p> <ul> <li>iOS build support using CMake</li> <li>A flexible system that allows Panda to either run in a dedicated app or run alongside other UIKit elements</li> <li>Improved multi-touch support</li> <li>Documentation and unit testing</li> </ul>

This project focuses on upgrading high-impact modules in Drupal to be fully compatible with the upcoming Drupal 11 release. The work includes identifying deprecated code, replacing it with supported APIs, writing automated tests, and ensuring backward compatibility. The deliverables will be high-quality, merge-ready module upgrades that support the Drupal ecosystem and reduce technical debt. The upgrades will follow Drupal's coding standards and be closely coordinated with module maintainers.

<p>My previous GSoC project resulted in OpenCV DNN module. It was the first step towards deep neural network support in OpenCV. However, neural networks world is developing rapidly, so dnn module should satisfy the requirements of the society. There are many enhancement ideas. I believe that their implementations are needed to the module or at least they will be definitely beneficial for it.</p>

<p>This project aims to optimize the WebAssembly version of OpenCV.js. Some evaluation experiments have shown that current WASM SIMD version has some problems, e.g. low performance of the kernel cvtColor and resize. The goals of this project can be summrized like the following points:</p> <ol> <li>Make OpenCV.js support 64-bit intrinsics. </li> <li>Fix the low performance of cvtColor and resize kernels.</li> <li>Optimize the perf tests for kernels to have better code reuse.</li> <li>Do perf tests for more kernels of module imgproc, dnn, and objectdetect, e.g. Sobel, Scharr, blur, and so on.</li> <li>Create a detector in OpenCV.js to check the ability of SIMD on the browser, and create a loader to load the corresponding version of OpenCV.js: Normal version, or WASM version.</li> </ol>

<p>OpenWISP Notification Module will provide a means of generating and transmitting notifications in OpenWISP modules. The module will play a significant role not only in OpenWISP Monitoring but also in OpenWISP Controller and OpenWISP Network Topology.</p> <p>The goal of this project is to develop the <a href="https://github.com/openwisp/openwisp-notifications" target="_blank">openwisp-notifications</a> module and integrate it into OpenWISP eco-system.</p>

<p>Fractal currently supports only one account, if you want to be connected at the same time with different accounts the user has to launch several instances. I would implement multi account support in the client so users can have more than one account connected at the same time with a user friendly interface. I would need to work with GNOME's design team to come up with the interface. To add multi account support first there is some work on the backend to do, then we can work on the interface. I will take the fractal-next branch as the basis for this work.</p>