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<p>This project aims to add support for File Loads method of inserting data into BigQuery for streaming pipelines. The PR - <a href="https://github.com/apache/beam/pull/7655" target="_blank">#7655</a> for <a href="https://issues.apache.org/jira/browse/BEAM-6553" target="_blank">[BEAM-6553]</a> added support in the Python SDK for writing to BigQuery using File Loads method for Batch pipelines. However, support still needs to be added for Streaming pipelines.</p> <p>Streaming pipelines with non-default Windowing, Triggering and Accumulation mode should be able to write data to BigQuery using file loads method. In case of failure, the pipeline should fail atomically. This means that each record should be loaded into BigQuery at-most-once.</p> <p>The JIRA issue for this project is <a href="https://issues.apache.org/jira/browse/BEAM-6611" target="_blank">[BEAM-6611]</a>.</p>

<p>JdeRobot is a software development suite for robotics, home-automation and computer vision applications. These domains include sensors (for instance, cameras), actuators, and intelligent software in between. It has been designed to help in programming such intelligent software. Details for the project: Project #5. Teaching Robotics: Translation of a Scratch program to ROS python components Scratch is a free visual programming language used in children's education, to teach them basic programming. It is composed of graphical building blocks (instructions) that must be visually connected to build the program. The idea here is to take benefit of our experience translating from a graphical description of a program in visual HFSM into a JdeRobot-ROS component to do the same with a different visual language, Scratch. The goal is to explore the use of Scratch with robots, both simulated or real, that JdeRobot-ROS allows and simplifies. We will start with simulated robots in Gazebo, despite with real robots will be the same as they use the same interfaces. This project expects to develop a new tool prototype that reads Scratch programs and translate them into ROS Python components.</p>

"Cockpit navigator" is a featureful File System Browser for Cockpit, which allows the user to remotely browse, manage, edit, upload, and download files on the server through the web browser. The project is about modernizing this plugin by following some new designs and rewriting the codebase to follow the standards specified by the starter-kit plugin. The project includes porting to React, adding tests, updating Patternfly, and much more.

The existing End-to-End (E2E) tests for the new React front end are hindered by low coverage and instability, compromising the reliability of the application. This project is dedicated to significantly improving E2E test coverage, ensuring comprehensive validation of the entire application workflow. By enhancing these tests, we aim to verify the seamless integration of components, ensuring the application functions correctly and reliably from the user's perspective.

The Karmada project consists of several components (e.g., controller-manager, scheduler, karmada-search, etc.), each accepting various command-line flags for configuration. These flags come from multiple sources: third-party dependencies (e.g., Kubernetes, controller-runtime) and custom flags defined by Karmada itself. During dependency upgrades or internal refactoring, flags can be unexpectedly added, removed, or modified, potentially impacting users who rely on specific configurations. This project aims to create comprehensive documentation and tooling to track and document all flags for Karmada's maintained components, establishing a baseline to detect and manage flag changes carefully. Expected Outcome: 1. Comprehensive flag documentation for all Karmada components (controller-manager, scheduler, karmada-search, webhook, aggregated-apiserver, descheduler, metrics-adapter, scheduler-estimator) 2. Automated flag extraction and documentation generation tool 3. CI/CD pipeline integration to detect and alert on flag changes 4. Documentation of flag lifecycle management (deprecation, removal)

<p>This project aims to focus on some of the primary goals the repo orcamap-react needs to support the visualization of hydrophones, orca calls, ships, sightings (can be weather, and ocean natural phenomena, too) and increasing the engagement of users with the feature to subscribe for further notifications. Developing different layers as a reusable component to onboard different data will be helpful to reuse them with other projects too (like orcasite and shipnoise).</p>

<p>P2PSP.org is a nonprofit organization that develops the P2PSP protocol, an application layer protocol designed for the real-time streaming of multimedia content over the Internet. I would like to contribute to the idea of <strong>Virtual Room</strong> this summers and be a part of the community. Recently I have been involved with a lot of real time applications .The hidden motivation behind choosing this project is mainly due to an application I recently developed, Latch for a hackathon. It is a Location based chat application, using Django as the primary backend server and Node.js for real time data handling. I already had an idea of developing a similar video based application which introduced me to WebRTC. I saw this project of Virtual Room in P2PSP, and the idea of an open source real time video streaming application fascinated me a lot. I believe that it could be very useful and can create an impact on the community.</p>

The component-model proposal merges and supersedes the Module Linking and Interface Types proposals. With this feature, WasmEdge can execute multiple modules wasm with Module Linking and and more flexible types with Interface Type.

This project aims to extend API Dash by adding support for WebSocket, MQTT, and gRPC, enabling developers to work with multiple modern communication protocols within a single tool. It will introduce a modular, protocol-agnostic architecture along with intuitive UI components for real-time and streaming workflows. Additionally, a CLI will be developed to support headless usage . The focus will be on performance, usability, and seamless integration with the existing API Dash ecosystem.

<p>This proposal aims to implement an OAI-PMH component for Apache Camel. OAI-PMH is a protocol widely used in libraries and digital repositories across the world. This implementation will be extremely useful for final users working on data integration this domain.</p>

<p>Exporting chats is an easy way to save conversations into the disk, which can be archived or shared with outsiders. This feature will be handy for users who have millions of messages and can’t easily access the oldest parts of their messaging history. As Matrix also provides end-to-end encryption via the Olm and Megolm cryptographic ratchets, the process will include decryption of messages. I will be using matrix-react-sdk and matrix-js-sdk, which provide adequate functions and methods to communicate with the server, handle encryption and build a very feature-rich export tool.</p>

<p>Casbin is an authorization library. Its support for diverse programming languages, different access control models and the powerful adapters gains it the greatest popularity in the open source community. However, there are still lots of difficulties in utilizing Casbin at the frontend, especially applying it on the management of users’ accessibility to specific UX widgets. In the GSoC 2020, I wish to implement a friendly JS library (aka Casbin.js) and other supported facilities to extend Casbin to the frontend development. This project mainly includes a plug-and-play Javascript library that supports for seamless connection with server, auto page controlling and the corresponding components and plugins for modern frontend frameworks.</p>

The Mifos Gazelle Profile/Demo Creator project aimed to improve the deployment experience and simplify environment configuration for demonstrations and storyboarding. The main deliverable was a sophisticated demo-creator tool that allows organizations to set up Mifos Gazelle with custom deployments and create tailored demo data files for specific use cases and scenarios

<p>Balrog is the software that runs the server side component of the update system used by Firefox and other Mozilla products. It helps ship updates faster and with much more flexibility than it's predecessor AUS (Application Update Service). However, Balrog's Admin API is mostly hand-written code, with some usage of wtforms for validation. It largely works, but it has some rough spots and inconsistencies. The move to an OpenAPI Specification will have multiple benefits including less code maintenance, multiple UI and backend bug fixes, better documentation and easier for clients to visualize and interact with API’s resources. Connexion, a framework designed for flask-based applications, will be used to handle HTTP requests based on OpenAPI Specification of the API to map the endpoints to the Balrog’s existing methods for serving the requests.</p>

skpro's probabilistic regressors have limited online/streaming support: only 3 of 20+ regressors implement update(), few meta-strategies exist, and there is no model persistence. This project adds: 1) native _update() for regressors with incremental APIs (NGBoostRegressor, BayesianLinearRegressor, BaggingRegressor) 2) composable meta-strategies (OnlineSlidingWindow, OnlineBatchMixture, OnlineExponentialForgetting) usable with any regressor 3) update() propagation through Pipeline and TransformedTargetRegressor 4) save()/load() ported from sktime's serialization pattern

The motivation behind this project is to extend and introduce a fully functional MCP server for pgmoneta. To achieve this ultimate goal, we have identified a set of subgoals that will transform the current implementation into a production ready system: Introduce Non-Blocking I/O for Intensive I/O Operations (e.g Backup). Architectural Abstraction refactoring via the Rig Framework. Production-Level Security & Authentication. Knowledge Retrieval via MCP Resources. Testing and Documentation

Cancer patients navigating clinical trial databases face complex search interfaces with dozens of technical filters, making it difficult to find relevant trials without medical expertise. This project builds a patient-facing clinical trial chatbot with an interactive map that removes this barrier through natural language. The system features a three-panel interface: a chat panel powered by an LLM agent that elicits patient information and matches it against the Cancer Trials Canada database, an interactive map that displays geocoded trial site locations and a summary panel that shows trial details when a pin is clicked Built using Chainlit server mounted inside FastAPI, React application with Mapbox GL for the interactive map. Trials are stored in PostgreSQL with pgvector for semantic and full-text search. An open-source LLM served via Ollama and Pydantic-AI. Multi-layered guardrails prevent off-topic or harmful responses, RAGAS for evaluation and Langfuse for observability and tracing throughout development.

The project aims to implement a Virtual Digital Audio Interface (DAI) for the Sound Open Firmware (SOF) to facilitate debugging, rapid prototyping. The Virtual DAI will support two directions: playback, which consumes data similarly to /dev/null, and capture, which generates data like /dev/zero or /dev/urandom. Expected outcomes include successfully merging the Virtual DAI component upstream, enabling simple playback and record pipelines, logging and discarding output frames for playback, and generating zero-filled frames for recording.

This project aims to improve playlist management in ListenBrainz by making it easier for users to search, organize, and interact with their playlists. Currently, while some backend support exists, the user experience lacks intuitive features for managing personal playlists effectively. To address this, I plan to implement four main features. First, I will complete and enhance playlist search directly on the user playlists page. Second, I will introduce tag-based organization, allowing users to categorize and filter playlists efficiently. Third, I will add in-playlist track sorting options such as sorting by title, artist, date added, and shuffle. Finally, I will enable users to view their MusicBrainz collections as playlists and optionally save them within ListenBrainz. The project will involve backend changes such as adding new database tables and API endpoints, along with frontend integration using React to provide a smooth and consistent user experience. The final deliverables will include a fully functional playlist search feature, tag-based organization system, track sorting functionality, and MusicBrainz collection integration, along with tests and documentation for all components.

<p>vcf-validator is a suite of command-line tools that can validate and fix VCF files. The goal of my project is to overcome the limitations of the validation suite that restrict its suitability for users with a less technical, more biological profile. I would perform the following tasks:</p> <p>The suite is hard to compile for non-Linux operating systems. Gradually the user bases of Windows and MacOS X are growing, and a simple concise way of building the tool must be provided to the users. To accomplish this, I aim to simplify the build process for Windows and MacOS X.</p> <p>Currently, the suite is completely terminal-based and can only read from and write reports to local files and needs to be installed and executed in the user’s machine. To deal with this, I aim to provide a network interface to run the suite as a service that would allow users to validate their own remote files, or a dynamically generated VCF stream.</p> <p>If the input VCF is compressed, it is the user's responsibility to decompress it. My task is to reduce this extra step by making the validator itself capable of decompressing such files.</p> <p>I would investigate how to insert checksums of reference genome sequences in the VCF header.</p>

The project has the aim of providing offline data entry capability into the CARE form-based data collection system. Currently, users experience interruptions when network connectivity is lost, preventing data entry while in the field with the application opened in a disconnected state. This project will maintain coordination with CARE forms during offline status, allowing users to continue using the app normally.The approach will implement an offline-first architecture that includes application caching, local storage, and sync capabilities. I plan to implement caching while using Workbox and Service Workers to cache the appropriate application assets and form definitions so that the user interface can load and continue to operate without a network connection. I plan to use IndexedDB, managed through Dexie.js, to store the form responses as local data storage on the user’s device. After connectivity is re-established, an automatic background sync process will use React Query and PQueue to ensure reliable and conflict-free data sync with the established database on the central server. Conflict resolution strategies will be included to maintain integrity, safe and complete data from being 'lost' when multiple users could be updating the same data at the same time.

<p>The Haskell Language Server is a popular, comprehensive Haskell IDE; however, it is yet to implement a core feature: symbol renaming. With the recent addition of HieDB (a database for references in Haskell code), there is sufficient infrastructure to implement this feature.</p> <h3>Problem Benefits</h3> <p>Having an accessible renaming feature could encourage improving names, leading to clearer naming across the Haskell community. Renaming is especially useful in Haskell since short names are common, meaning they are often reused and difficult to disambiguate when renaming manually.</p> <h3>Project Aims</h3> <pre><code> - To support workspace-wide renaming of all names, including type synonyms, data constructors, and functions. - To support renaming of qualified imports. </code></pre>

This project involves the integration of AlphaMissense, an innovative tool for predicting the pathogenicity of missense mutations, into two established platforms: Genome Nexus and cBioPortal. My Objectives and Deliverables are: - Integrate AlphaMissense pathogenicity predictions into Genome Nexus API responses, enriching genetic variant analysis with detailed pathogenicity scores. - Display AlphaMissense predictions within the Genome Nexus variant pages and add dedicated data columns in the cBioPortal mutation tables, complete with functionalities for sorting, filtering, and downloading. -Add AlphaMissense pathogenicity prediction and score into Genome Nexus annotation pipeline as two new columns in the annotation result file The project will be executed in phases, starting with initialization and planning, followed by backend and frontend development to integrate and visualize AlphaMissense data. Subsequent phases will focus on testing, deployment, and documentation, concluding with a final review and official launch. Post-launch, the project will enter a maintenance and support phase to address any arising issues and incorporate user feedback. Backend development will utilize Java and Spring Boot for integrating the AlphaMissense plugin into the Genome Nexus API. Frontend components will be developed using React and TypeScript, ensuring a dynamic and user-friendly interface for displaying genetic predictions.Comprehensive testing phases, including unit, integration, and User Acceptance Testing, will ensure the reliability and accuracy of the integration. This integration represents a significant leap forward in personalized medicine. By making pathogenicity predictions more accessible and interpretable, this project aims to support advancements in genetic research and clinical decision-making, ultimately contributing to improved patient outcomes.