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This proposal addresses the need to provide game developers with a Vibe Coding Agent, an intelligent assistant capable of generating assets, writing code, and automating the Godot editor from natural language to complete complex tasks. To support this, it develops a decoupled, CPython-based framework. The solution includes a native GDScript editor plugin that captures scene context and communicates via non-blocking asynchronous HTTP requests, paired with a powerful FastAPI backend. This backend utilizes Pydantic for strict schema validation, an Agentic Core to translate user prompts into structured actions, and a Persistent Memory module to maintain project state across editing sessions. Deliverables include a non-blocking Godot plugin, the CPython backend planning layer, initial implementations for the Agentic Core and Persistent Memory, a virtual container for safe code execution, and comprehensive documentation and tests.

This project aims to enhance QEMU's HP PA-RISC emulation by implementing LASI Network Card and NCR 710 SCSI Controller device models. LASI Network Card: Debug, test and complete the current Intel 82596 based implementation to provide full functionality NCR 710 SCSI Controller: Develop a new, accurate QEMU device model based on documentations present. Deliverables: Fully functional LASI Network Card and NCR 710 SCSI Controller models.

Shardingsphere federated query engine provides support for SQL statements. In the GSoc period, I have to add support for more MySQL SELECT statements so that more SQL statements can be converted into SQLNode. This can be achieved by: 1- Analysing the SQL statement I have to add support of, 2-Figure out components & logic required , 3- Make changes in SQL federation engine optimizer files , 4- Optimize parser files , 5- Make changes in TEST files to ensure test is passing successfully. After the support for More SELECT statements queries is added, The users & developers will be benefitted by utilising more SELECT queries for MySQL .

TensorFlow Decision Forests (TF-DF) is a collection of state-of-the-art algorithms for the training, serving, and interpretation of Decision Forest models. Unfortunately, the lack of detailed examples in the community is preventing many people from fully realizing its potential. In this project, I will introduce a series of examples that will demonstrate the use of TensorFlow Decision Forests on various datasets. I’ll dive into beginner as well as intermediate examples that will help improve the performance of these tools on structured datasets.

<p>I propose my project idea relating to Apache APISIX growth, titled <strong>"Redesign, develop and refactor Apache APISIX landing page and documentation website"</strong>. Main reasons for me to propose this project are -</p> <ul> <li>Website doesn’t show the most important features of APISIX</li> <li>Website lacks a secondary call-to-action (After download) to the docs for which the website is made for.</li> <li>Website lacks the amount of information needed to explain the usefulness of APISIX and why it is better.</li> <li>The copywriting in certain sections of the website is too long (description section)</li> <li>Website lacks accessibility in images. For instance, the APISIX architecture image is not clear on desktop.</li> <li>Website lacks visual design as a whole, when compared to other SaaS product websites.</li> </ul> <p>Considering the above issues, it is essential that a redesign is needed to solve this, because to solve them would require a rework of the design and copywriting in the website.</p>

<p>directlabels is an R package for adding intuitive text labels to plots, typically in order to replace confusing legends in lattice and ggplot2. This project will incorporate several modifications to this package which will make it more attractive and convenient to use/test this package via better documentation and tests.</p> <p>The improvements include:</p> <p>• Creation/Configuration of software for automatic generation of a new documentation website (hosted on GitHub pages, instead of the current r-forge domain), thus removing the need to re-compute the docs manually. (I'll be using a combination of dldoc and GA-based workflows)</p> <p>• Addition of directlabels to the ggplot2 extensions gallery.</p> <p>• Refactoring the codebase to make it eligible to exercise grid.force by using the new (Rversion &gt;= 3.0.0) grid hook methods and by making changes to the functions affected by this transition.</p> <p>• Setting up code coverage (possibly automating this as well) and a proper testing framework, with tests based on the grid graphical objects which are exposed via grid.force from the transition to the makeContent hook.</p>

<p>Newt supports the Process Description (PD) and the Activity Flow (AF) graphs of SBGN. However, there is no conversion between these two graphs in the Newt. PD is a detailed version of AF. Thus, from PD, AF can be obtained but not vice versa. There is already a library for converting PD to AF. The goal of this project is to host a service for this converter and then integrate it into Newt.</p>

<p>This will be a continuation of the previous summer’s <strong>Outliner Improvements</strong> project. With selection now syncing between the outliner and other editors, other improvements can be made to the outliner to increase usability. These include changes to the context menu, a connection with the properties editor tabs, manual object sorting, and increased control over selection and activation of data types.</p>

<p>Aim of this project is to develop a People Identification System with the following two capabilities.</p> <ol> <li>Given an image identify all the faces in it and return labels of identified people. </li> <li>Classify new persons and use incremental learning techniques to recognize it later.</li> </ol> <p>This component will allow for a more enriched interaction between robots and humans by enabling robots to make better decisions based on the input from different categories of people.</p>

<p>Fedora has an android app which lets a user browse Fedora Magazine, Fedora Ask, Fedocal etc within it. This app is build using the Ionic Framework, Angular and Cordova. Essentially it is a cross-platform hybrid app.</p> <p>In the current form, most of the functions rely on an in-app browser to render content. This project aims to improve the existing Fedora App for Android for speed, utility, and responsiveness, introduce a deeper native integration and make the app more personal for the user.</p>

<p>The Haskell IDE Engine is a Haskell backend for IDEs, which utilises the Language Server Protocol to communicate between clients and servers.</p> <p>This projects aims to create a test framework that can describe a scenario between an LSP client and server from start to finish, so that functional tests may be written for the IDE engine. If time permits, this may be expanded to be language agnostic or provide a set of compliance tests against the LSP specification.</p>

<p>PyNN is a project written in python that aims at interfacing a handful of neural network simulators. A unified high level interface means that a model can be configured easily and only once and then it can be deployed on all supported simulators. Different simulators provide diverse features and also might use various numerical approaches and approximations leading to possibly different results. Having an option to compare data from several simulators without extra work is a great feature PyNN offers.</p> <p>GeNN is an efficient neural network simulator written in C++. The characteristic feature of this simulator is the ability to run simulation on GPU thus greatly decreasing required computational time.</p> <p>Interfacing GeNN from PyNN would be a valuable acquisition for both projects. PyNN will have another, faster simulator at hand and GeNN will get a python interface. Python is much more widespread among the neuroscientists. Having such an interface will help to make GeNN more popular and hopefully will reduce the time scientists spent on their simulations.</p>

<p>Implement the project idea <a href="https://wiki.postgresql.org/wiki/GSoC_2018#Sorting_algorithms_benchmark_and_implementation_.282018.29" target="_blank">sorting algorithms benchmark and implementation (2018)</a></p> <p>Candidate sorting algorithms:</p> <ul> <li>Introsort</li> <li>Timsort</li> <li>Dual-pivot quicksort</li> <li>Radixsort</li> </ul> <p>Use cuckoo hashing as the new hashing table implementation</p>

<p>Inside this proposal, I introduce my project goals of GSoC 2017 and bring out a tentative timeline to achieve them. To make sure I can finish it in this summer, I focus on the basic features.</p>

<p>Creating a generic mechanism that allows users to annotate domain objects with text labels/tags. It has several uses such as, for grouping data and generating work-queues.</p>

<p>The Open Event Project offers event managers a platform to organise all kinds of events including concerts, conferences, summits and regular meetups. The components support organisers in all stages from event planning to publish, marketing and ticket sales. Automated web and mobile apps help attendees to get information easily. My project is to add Open Event format support in other Open Source Event Apps.</p>

<p>The goal of this project is to develop a framework for the development and presentation of interactive tutorials in order to provide a full learning experience.</p>

<p>Ahmia is a working search engine that indexes, searches, and catalogs content published on Tor Hidden Services. Furthermore, it is an environment to share meaningful insights, statistics and news about the Tor network itself. In this context, there is a lot of work to do.</p> <p>During GSoC, I plan to work on several aspects of this search engine from fixing bugs to improving search results.</p> <p>First I’m going to start working on bugs and automation so users and developers can see immediate results and so I can learn my way around the codebase quickly.</p> <p>Then I will start developing new features like search commands, additional search results information (like screenshots). I will also work a lot on improving the search results.</p> <p>Finally I will work on statistics which is not an easy problem when you also want to respect privacy.</p> <p>I also have a couple ideas for optional goals or additional projects I could make after GSoC is done.</p>

<p>The GTK client (Tryton) already has CSV Import/Export feature. This project would implement the same feature in web client (SAO) keeping the behavior similar.</p>

<p>OSM2World provides an excellent tool for converting OSM data to 3D models. It however lacks in visual fidelity, which can make it off-putting to use by itself, and more difficult to coordinate it with and external rendering program such as POVRay. This proposal suggests several modern OpenGL shaders to improve the visual fidelity of OSM2World.</p>

HiperHealth's clinical pipeline currently lacks visual diagnostic capabilities. This project adds a modular MedVision skill channel, an external, installable module that brings medical image analysis into the existing pipeline with zero core modifications. The project delivers shared infrastructure (MONAI preprocessing, Grad-CAM explainability, structured Pydantic output models, confidence calibration) and two body-region skills: SkinAnalysisSkill (DINOv2 backbone, ISIC 2018 dataset) and a second body-region skill (Eye/Nail) to validate extensibility. Each skill automatically enriches the DiagnosticsSkill's differential diagnosis via the prompt_fragments mechanism, producing calibrated predictions with saliency maps for clinical transparency. The project includes Fitzpatrick fairness auditing and ≥90% test coverage.

Automotive Grade Linux's modern Flutter UI framework lacks native Bluetooth connectivity. The legacy Bluetooth services cannot be reused because they depend on afb-daemon, unavailable in the current runtime. This project builds a native C++ Bluetooth plugin bridging Flutter with the open-source BlueZ stack via typed MethodChannels. Deliverables include a Yocto layer for system dependencies, a reliable Bluetooth abstraction library, a reactive settings UI for device pairing, and A2DP/AVRCP integration in the media player. Stretch goals include HFP telephony, PBAP contacts, and MAP messaging. This demonstrates production-grade automotive audio routing using purely open-source technologies.

The Virtual Brain (TVB) provides an open-source simulation framework for whole-brain network modeling. Unlike the traditional approach of using neurons at micro-scale level, TVB takes into account the brain regions and their interactivity. This proposal aims to enhance the TVB ecosystem by developing and improving interactive JupyterLab widgets — BCT metrics projection viewer, Connectivity_react widget and Unified Head widget. The new widgets proposed will extend TVB's analytical capabilities and improve the overall user experience for researchers studying large-scale brain connectivity patterns.