Application for Google Summer of Code 2024 is now closed. See official Google Summer of Code site.
See official accepted projects and contributors for the list of projects this year.
Rocket.Chat is proud to be a participating mentoring open source organization for Google Summer of Code 2024, helping to usher in a new generation of open source contributors and enthusiasts.
For timeline, see Official Google Summer of Code 2024 Timeline for more details.
Almost anyone in the world over 18 years of age who loves coding and wants to explore the incredible world of open source can join us as a GSoC 2024 contributor.
Most exciting news for the 2024 season is a new focus on ML/AI projects, and the introduction of a small project type with a 90 hours duration; allowing participation from those who can only devote part of their summer to exploring open source.
For details and rules of Google Summer of Code 2024, please see the GSoC 2024 Official Website. For timeline, see Official Google Summer of Code 2024 Timeline for more details.
For general information, please visit our 24 x 7 community channel for Google Summer of Code 2024 : https://open.rocket.chat/channel/gsoc2024
Join our Google Summer of Code 2024 Team today, introduce yourself to the friendly community, and interact with over 636 like-minded contributors/mentors and meet the team in the 50 team channels.
If you have ideas and proposals that are not on our idea list, or if a mentor is not available, you can also email to:
But better yet, you can post your idea in the New GSoC 2024 Ideas looking for mentors channel and possibly getting some immediate community feedback or support for your idea.
Interested contributors are also encouraged to interact directly with our team and community on the team channels:
https://open.rocket.chat/channel/gsoc2024/team-channels
As well as on GitHub:
https://github.com/RocketChat/Rocket.Chat
Those who prefers forums can post messages on our GSoC forum channel (although as the leading open source team chat project we prefer you use Rocket.Chat channels above to reach us instantly).
Results for 2024 has just been announced on May 1, 2024. This is an incredible year for GSoC at Rocket.Chat. Thanks to the enthusiastic early interests from new contributors and extremely strong support of returning community mentors, Google has graciously selected seventeen Rocket.Chat projects.
Mentors of selected projects will start welcoming the contributors officially and bringing them into our community bonding activities immediately. An incredible 14 mentors this year are returning GSoC contributors from prior years; we sincerely thank them for their ethusiastic support.
All of the 17 projects are open source projects welcoming additional contributors. Please click on links below and start contributing!
| Contributor | Project | Mentors |
|---|---|---|
| Abhi Patel | Multiple files in one message | DhruvJain, Rodrigo Nascimento |
| Akshun Kuthiala | API Documentation Generator | Guilherme Gazzo, Rodrigo Nascimento |
| Aman-Negi | AI in-channel GIF Image Generator | Nabhag Motivaras |
| Anjaneya Gupta | Google Summer of Code Community Hub 2024 | M. Palanikannan |
| Ashutosh Singh Chauhan | Extended LLM Prompt Editor/Explorer | Gabriel Engel, Shubham Bhardwaj |
| Hardik Bhatia | Agile BOT | Gabriel Casals, Felipe Scuciatto |
| Hunter Xia | AI Query Bot: a configurable Retrieval Augmented Generation pipeline executor | Shiqi Mei |
| Jeffrey Yu | AI Chat Conversation Thread Summarizer | Dnouv, José Petry |
| Maria Khelli | Smart Scheduling App Assistant | Douglas Gubert, Dnouv, Sing Li |
| Prisha Gupta | AI Assistant to help with understanding Rocket.Chat core codebase | Vinayak_Sharma |
| Ryan Zhou | AI C/C++, Java, Javascript, Typescript, Python Programmer | Mustafa Hasan Khan, Samad Yar Khan |
| Sandeep Pillai | AI In-message Emoji generator / embellisher | Sing Li, Shubham Bhardwaj |
| Sayan_Banerjee | Graphical Guided RC Code Tours | AdityaSingh-02 |
| Umang Utkarsh | News Aggregation App | abhinavkrin |
| Vipin Chaudhary | Quick Replies Functionality in RocketChat | Gabriel Casals, Hugo Costa |
| Yuriko Kikuchi | AI Newsletter Generator and Publisher | Dnouv, Douglas Gubert |
| Prisha Gupta | AI Assistant to help with understanding Rocket.Chat core codebase | Vinayak_Sharma |
| Zishan_Ahmad | Embedded Chat 2024 | Sidharth Mohanty |
Application submissions official closed on April 2nd, and we have received a total of 225 proposals from our ethusiastic GSoC 2024 contributors community. In the next few weeks, project mentors will be combing through these proposals and reviewing them for selection. Meanwhile, open source contributions continue and we will be running our tenth instance of the hands-on workshop "Write an AI Rocket.Chat App in an hour". To thank our code contributors, we are also running a special "thank you" activity for all code contributors having at least one PR merged this season.
Check out our GSoC 2024 Contributors Leaderboard, to see the amazing contributions by our GSoC 2024 community: 264 new contributors creating 102 Merged PRs, 94 Open PRs, and 249 Issues. as of April 3, 2024!
Returning GSoC community mentors helped us to run the ninth iterative refinement of the "Write an AI Rocket.Chat App in an hour" on March 29, 2024 to a room full of attendees. The session is hands-on, and we have improved it by adding more information on the use of UIKit from prior session feedback. Thanks goes to the ninth set of ethusisastic attendees for providing us with more valuable feedback.
We are thankful to have EIGHT former Rocket.Chat GSoC Alumni from as far back as SIX years ago returning this year to guide, influence and inspire this year's new contributors at the Rocket.Chat Google Summer of Code Alumni Summit 2024 on March 25, 2024. Event was well attended (over 50) and the recorded proceedings is now available here to benefit all GSoC 2024 participants. We like to thank all of the returning alumni, and all of the contributors for attending this online event.
Check out our GSoC 2024 Contributors Leaderboard, to see the amazing contributions by our GSoC 2024 community: 239 new contributors creating 98 Merged PRs, 97 Open PRs, and 247 Issues. as of March 24, 2024!
GSoC 2024 community mentors continued to help us to run the seventh and eight iteration of the "Write an AI Rocket.Chat App in an hour" on March 15, 2024 and March 22, 2024 to a full house of attendees (we have increased capacity to 40+ attendees for recent sessions). The session is hands-on, and we are doing everything we can to ensure every attendee recieves the same learning experience. Thanks goes to the seventh and eighth set of ethusisastic attendees for providing us with valuable feedback.
Check out our GSoC 2024 Contributors Leaderboard, to see the amazing contributions by our GSoC 2024 community: 189 new contributors creating 73 Merged PRs, 104 Open PRs, and 224 Issues as of March 7, 2024!
GSoC 2024 community mentors continued to help us to run the sixth iteration of the "Rocket.Chat App workshop (Write an AI App)" on March 1, 2024 to a full house of attendees. The session is hands-on, and we have to limit the quota due to server and AI/GPU resources available. We have modified the flow to include debugging and log content ahead of the workshop, enabling attendees to debug their setup in case of difficulty during the session. Due the overwhelming response, we will be expanding our capacity for the next session. Thanks goes to the sixth set of ethusisastic attendees for providing us with valuable feedback.
Check out our GSoC 2024 Contributors Leaderboard, to see the amazing contributions by our GSoC 2024 community: 141 new contributors creating 62 Merged PRs, 103 Open PRs, and 203 Issues as of February 24, 2024!
Returning GSoC mentors have helped us to run the fifth iteration of the "Rocket.Chat App workshop (Write an AI App)" on February 23, 2024. The session was one of the best attended session as we tightened the pre-requsite preparation with the attendees and experimented with different delivery strategies to ensure the best learning experience for all. We have also added new AI content now that the content delivery has stablized. Thanks goes to the fifth set of ethusisastic attendees for providing us with valuable feedback
2024 GSoC mentors have helped us to run the fourth iteration of the "Rocket.Chat App workshop" on February 16, 2024. The session was well attended as we continued our experimentation with different delivery strategies to ensure the best learning experience for all. Thanks goes to the fourth set of ethusisastic attendees for providing us with valuable feedback.
Returning GSoC mentors have helped us to run the third iteration of the "How to build a Rocket.Chat App workshop" on February 9, 2024. The session was well attended as we experiment with different delivery strategies to ensure the best learning experience for all. Thanks goes to the third set of ethusisastic attendees for providing us with valuable feedback
Check out our GSoC 2024 Contributors Leaderboard, to see the amazing contributions by our GSoC 2024 community: 95 new contributors creating 57 Merged PRs, 85 Open PRs, and 171 Issues as of February 8, 2024!
A group of returning GSoC mentors has help us to put together and launched the second instance of the "How to build a Rocket.Chat App hands-on workshop" on February 2, 2024. The session was filled within 24 hours of announcement. Thanks goes to the second 15 ethusisastic attendees for providing us with valuable feedback for improvement. We intend to refine this workshop over the GSoC 2024 season and will be running incrementally improving instances weekly throughout Feb and March.
Check out our GSoC 2024 Contributors Leaderboard, to see the amazing contributions by our GSoC 2024 community: 63 new contributors creating 42 Merged PRs, 65 Open PRs, and 118 Issues as of January 28, 2024!
We launch the very first instance of "How to build a Rocket.Chat App hands-on workshop" on January 26th, 2024. This workshop is created by a panel of our community mentors and is intended to prepare our contributors for their Google Summer of Code 2024 contributions. The workshop was over subscribed upon announcement. Thanks to the first 15 ethusiastic attendees. We intend to refine this workshop over the GSoC 2024 season and will be running incrementally improving instances weekly in Feb and March.
Check out our GSoC 2024 Contributors Leaderboard, to see the amazing contributions by our GSoC 2024 community: 45 new contributors with 24 Merged PRs, 50 Open PRs, and 75 Issues as of January 15, 2024!
This is the GSoC 2024 project ideas list for Rocket.Chat.
👥 Mentor(s): Shubham Bhardwaj, Gabriel Engel
💬 Description:
A prompt editor is the quintessential development tool for any AI/ML prompt engineer. With ever-increasing number of Rocket.Chat users experimenting and developing with open source LLMs, it is important to have a great prompt editor at their disposal. This project includes the creation of a fully featured prompt editor as a Rocket.Chat app. This editor should enable free conversation, by any designated/configured Rocket.Chat user, to chat with any open source LLMs (Mistral, Llama 2, Phi, and so on), and the ability to save (and manage - delete etc) all conversation history. It should also enable a Rocket.Chat users to "share" the prompt(s) to external applications. Initial implementation should be for the RC Web App (and Electron).
💪 Desired Skills: Rocket.Chat Apps development. LLM prompt editor dev experience.
🎯 Goals/Deliverables: Rocket.Chat App empowering users to converse freely with open source LLMs and save the conversations. The app must allow management of these prompts by the user, including deletion, renaming, and sharing of the prompt content via the clipboard or into the chat stream as a message.
⏳ Project Duration: 175 hours (Medium)
📈 Difficulty: Easy/Intermediate
👥 Mentor(s): Aditya Singh, Kevin Aleman
💬 Description: Most Rocket.Chat developers uses VSCode when studying our massive production code base, and when writing new code. VSCode is the best environment for conducting interactive tutorial and code walkthroughs. The CodeTour extension available in VSCode can be used to create such walkthrough and tutorials. This project involves the development of a set of guided tutorials using CodeTour that will help new developers to understand how to perform multiple actions. In 2024, we want to extend these tours to include graphical diagrams and flow charts.
Paths to be documented and graphically enhanced for 2024 include these areas:
- How a message is sent
- How to create an endpoint
- How to add a new service
- How to create a DB model
- How to use DB models
- How services interact between them
- How to build a lib
- How to navigate monorepo (where is everything, how's imported, etc)
We welcome any additional ideas you may have.
💪 Desired Skills: NodeJS, MongoDB
🎯 Goals/Deliverables: A set of guided tours from the topics described above
⏳ Project Duration: 90 hours. (Small)
📈 Difficulty: Easy
👥 Mentor(s): Abhinav Kumar
💬 Description: A Rocket.Chat app that collects news from top websites like TechCrunch, etc and sends its summary with a link to full content. The technical challenge would be to write different logic to collect news from different sources -> since some has API, some has RSS feed. These sources should be categorized and presented in a "newspaper" or "news feed" format. News sources and categories should be completely configurable.
💪 Desired Skills: Rocket.Chat App development.
🎯 Goals/Deliverables: A Rocket.Chat App that can presents users with daily news feed gathered from all over the Internet.
⏳ Project Duration: 90 hours (Small)
📈 Difficulty: Easy
👥 Mentor(s): Sidharth Mohanty
💬 Description: Improvement to the EmbeddedChat project this year includes:
- Creation of a Rocket.Chat App to remotely configure the associated EmbeddedChat instance(s).
- Security improvements for authentication (one such is providing endpoints using the created EmbeddedChat app for RocketChat to support cookie-based authentication instead of storing the token in localStorage).
- Improving the UI library by making it completely headless and adding different pre-built templates). Bonus: improvements in UI kit rendering inside EmbeddedChat
💪 Desired Skills: Rocket.Chat App development
🎯 Goals/Deliverables: Improved EmbeddedChat that can be configured on the associated Rocket.Chat instance and major security update which requires to completely shift from localStorage to browser cookies. Clean UI for EmbeddedChat and provide users with some pre-built templates so that they can easily get started with EmbeddedChat.
⏳ Project Duration: 175 hours (Medium)
📈 Difficulty: Easy/Intermediate
👥 Mentor(s): Vinayak Sharma
💬 Description: The code base of Rocket.Chat is known to be unwieldy and large, and typically takes a skilled developer months to become familiar with. The purpose of this project is to create a Rocket.Chat app that offers an AI assisstant chatbot that can help with the understanding and learning of the Rocket.Chat code base. This bot should be slash command or GUI accessible and be able to answer structural or logical question about Rocket.Chat's code and how certain workflows are performed within the codebase. Ideally it should also extract and reference the associated source code lines during its operation. It is suggested that a Retrieval Augmented Generation pipeline be used to populate a vector database with indexed chunks of the Rocket.Chat code base; generation should leverage open source LLMs (Mistral, Llama2, CodeLlama, WizardCode, Phi and so on). Research and experimentation with chunking strategy, vector search algorithms, and other RAG variables is expected.
💪 Desired Skills: Rocket.Chat App development. LLM prompt design/engineering. RAG pipeline design and development.
🎯 Goals/Deliverables: A AI assistant chatbot that any Rocket.Chat users can turn to when studying and trying to understand Rocket.Chat's huge codebase.
⏳ Project Duration: 175 hours (Medium)
📈 Difficulty: Easy/Intermediate
👥 Mentor(s): Hugo Costa, Gabriel Casals
💬 Description: Addition of a Quick Replies feature. This functionality would be similar to predefined answers in a helpdesk/support context, giving users the option to generate standardised responses. Some possible functionality: -Allow users to create and save a list of predefined quick replies. -These quick replies would be accessible through a simple button or keyboard shortcut. -Users could thus select a quick reply in lieu of manual text input, save time, and expedite the response process.
💪 Desired Skills: Familiarity with react and node; coding on typescript; AI will be a good addition.
🎯 Goals/Deliverables: Quick Replies feature
⏳ Project Duration: 175 hours. (Medium)
📈 Difficulty: Intermediate
👥 Mentor(s): Shiqi Mei
💬 Description: Create a Rocket.Chat app that answers queries by executing a configurable RAG pipeline. The RAG pipeline should be configurable via the App's setting - controlling aspects such a embedding/tokenizer engine, vector database search algorithms, re-ranking strategy, open source LLM used for generation (Mistral, Llama, Phi and so on); as well as any prompt used in the pipeline. The code should have at least two concrete config/examples within two non-trivial problem domains (feel free to use available public open source data collections).
💪 Desired Skills: Rocket.Chat App development. LLM prompt design/engineering. RAG pipeline design and development.
🎯 Goals/Deliverables: A flexible AI query bot for any problem domain that operates based on a pre-configured RAG pipeline.
⏳ Project Duration: 175 hours (Medium)
📈 Difficulty: Easy/Intermediate
👥 Mentor(s): Samad Khan
💬 Description: Bringing our Github App into the 2024 AI age, this project will add ability to provide a AI generated summary of PRs to the code reviewers whenever a link is shared for a PR. The AI assistant should also help in reviewing C/C++, Java, Javascript, or Python code; in addition to help find possible bugs in the code involved. The app should leverage modern open source LLMs (Mistral, CodeLlama, WizardCode, Llama2, Phi, and so on) to perform its tasks.
💪 Desired Skills: Rocket.Chat App development. LLM prompt design/engineering.
🎯 Goals/Deliverables: Github App now leveraging LLMs to perform code review, bug finding, and PR summarization.
⏳ Project Duration: 90 hours (Small)
📈 Difficulty: Easy
👥 Mentor(s): Carlos Suarez, Gabriel Casals
💬 Description: A UI kit is a set of files that contains critical UI components like fonts, layered design files, icons, documentation, and HTML/CSS files. We are looking to make the UI KIT DX better enhancing error boundary, option to send payloads from cloud and render UIKit components, additional input field types and validations
💪 Desired Skills: Familiarity with TypeScript, Javascript and React development
🎯 Goals/Deliverables: Improve UI Kit for Desktop, impacting different areas of Rocket.Chat
⏳ Project Duration: 175 hours. (Medium)
📈 Difficulty: Intermediate
👥 Mentor(s): Devanshu Sharma (@Dnouv)
💬 Description: Create a Rocket.Chat app that will translate messages within a DM channel between two parties communicating in two different languages. The app should demostrate not only translation of language, but also account for cultural differences and differences in sentiments. The app must leverage modern open source LLMs (Mistral, Llama2, Phi, and so on) in generating the translations.
💪 Desired Skills: Rocket.Chat App development. LLM prompt design/engineering.
🎯 Goals/Deliverables: A Rocket.Chat App that acts as a personal translator for cross-language and cross-cultural communications.
⏳ Project Duration: 90 hours (Small)
📈 Difficulty: Easy
👥 Mentor(s): Nabhag Motivaras
💬 Description: A slash command triggered Rocket.Chat app that will generate a small GIF image. The image generation should be controlled via a descriptive prompt issued by the user. The image can be inserted in-place within the chat or sent to the system clipboard. The app must leverage modern open source diffusion model such as Stable Diffusion in generating the image.
💪 Desired Skills: Rocket.Chat App development. Diffusion models prompting. Artistic inclinations.
🎯 Goals/Deliverables: A Rocket.Chat App that can generate arbitrary GIF images within a message, based on a descriptive prompt.
⏳ Project Duration: 90 hours (Small)
📈 Difficulty: Easy
👥 Mentor(s): Felipe Scuciatto, Gabriel Casals
💬 Description: Agile adoption is increasing year to year on the different industries. There is an opportunity to add agile package bots to help squad with reminders, links and facilitate attendance to meeting based on simple calendar inputs and emoji reactions. Candidate will be working with Agile experts and Engineers to build some solutions for this space and help improve team/squads productivity. Successful contributor will propose and implement a Chatbot that solves a problem in agile. Candidate have a free choice of technology to implement the chatbot - RASA, Botpress, Dialogflow, and so on.
💪 Desired Skills: Familiarity with TypeScript development. Demonstrated interest and/or passion in Agile and squad productivity tools.
🎯 Goals/Deliverables: A working chatbot that can improve agile team productivity
⏳ Project Duration: 175 hours (Medium)
📈 Difficulty: Intermediate
👥 Mentor(s): M. Palanikannan
💬 Description:
With last year's contributor returning as mentor for this project, we continue the work of crafting a "full stack component framework" in which a scalable website can be created by non-technical users using drag-and-drop components that not only include UI and client-side logic, but also pre-scaled server-side behaviors (or serverless impl). The ultimate use-case we have been working on is the community hub for Rocket.Chat Google Summer of Code. It will link all the despearate servers into one easy to customize and maintain uniform scalable web app (comprise of a set of full-stack components).
This year's work will be in the areas of 1. "syntax sweetening", moving all server-side customization and configurability into HTML-tag-like notation into the component layout files (in format that can be easily generated by WYSIWYG layout IDE). And 2. solving completely the "component initialization data definition and maintenance" problem
Desirable Skills: Advanced Typescript, Advanced Next.js, Npm, SWC, Turborepo, Golang.
Goal/Deliverable: A working Google Summer of Code Community Hub that put together using components layouts that have both syntax sweetening and easy to configure/change/maintain data initialization.
⏳ Project Duration: 90 hours (Small)
📈 Difficulty: Easy/Intermediate
👥 Mentor(s): Gabriel Engel, Sing Li
💬 Description: This Rocket.Chat app applies the latest web standard WebGPU technology to run AI Agents in-browser. The app should allow the execution of a subset of agents created by open source agent frameworks such as rubra.ai Catering for the limited GPU/LPU capacity of most 2024 client machines/devices, the agents may need to rely on new generation low resources reasonable quality open source LLMs (such as Gemma 2b and Gemma 7b, Phi, and so on). The app must include at least two specific use-cases where the application of client-side agents actually makes sense (or actually required). This project is perfect for a contributor who is already working day-to-day with modern LLMs, tracking their rapid progress, and is looking for a mild challenge.
💪 Desired Skills: Rocket.Chat App development. Thorough understanding of 2024 RAG pipelines. Familiarity with WebGPU and associated technologies.
🎯 Goals/Deliverables: A working Rocket.Chat App that can run agents in-browser using client-side GPU resources.
⏳ Project Duration: 175 hours (Medium)
📈 Difficulty: Intermediate
👥 Mentor(s): Debdut Chakraborty
💬 Description:
meteor-accounts is the largest Meteor dependency Rocket.Chat has as of today. This project will aim to remove all dependency of it from Rocket.Chat taking it further into the road of meteor-less-ness.
💪 Desired Skills: Familiarity with JavaScript and TypeScript is mandatory. Along with server side, may also need client side javascript skills. Meteor knowledge is a plus.
🎯 Goals/Deliverables: Rocket.Chat running without meteor/accounts package as a dependency.
⏳ Project Duration: 175 hours (Medium)
📈 Difficulty: Hard
👥 Mentor(s): José Petry
💬 Description: This Rocket.Chat app leverages modern open source LLMs (Mistral, Llama2, Phi, and so on) to summarize a conversation within a Rocket.Chat conversation thread. This summary should appear as either a private message to the invoking user, or become an in-line comment together with the discussion thread itself.
💪 Desired Skills: Rocket.Chat App development. LLM prompt design/engineering.
🎯 Goals/Deliverables:
A working Rocket.Chat App that can summarize any conversation threads.
⏳ Project Duration: 90 hours (Small)
📈 Difficulty: Easy
👥 Mentor(s): Dhruv Jain
💬 Description: Addition of a feature enabling possibility to send multiple files (text files, images, audio, videos) in a same message; similar to what is seen on many other platforms.
💪 Desired Skills: Familiarity with react and node; coding on typescript;
🎯 Goals/Deliverables:
Multiple files in a message feature.
⏳ Project Duration: 90 hours (Small)
📈 Difficulty: Easy
👥 Mentor(s): Aaron Ogle
💬 Description: Create a Rocket.Chat app that can be used to aggregate feeds from the Bluesky ecosystem (ActivityPub may need different non-client approach). User should be able to select and manage the feeds they are interested in. This project does not involve the posting/publishing of content to the federated networks.
💪 Desired Skills: Familiarity with JavaScript and TypeScript is mandatory. Rocket.Chat app development. Experience or familiarity with AT-protocol or ActivityPub.
🎯 Goals/Deliverables: Rocket.Chat app that aggregate feeds from Bluesky or Mastodon federated ecosystems.
⏳ Project Duration: 90 hours (Small)
📈 Difficulty: Easy/Intermediate
👥 Mentor(s): Guilherme Gazzo
💬 Description: Provide a better documentation for the UIkit, adding explanations about the "whys" and "hows". Most importantly, and the coding part of this project: coming up with some non-trivial working examples of concrete use cases.
💪 Desired Skills: Knowledge of TypeScript, JavaScript, React, and Rocket.Chat UIkit. Previous experience with UI framework or API documentation a big plus.
🎯 Goals/Deliverables:
The UIKit documentation improved with many coding examples and an understandable general overview, including:
- Reasons
- Explanation of each Block/Section
- Examples and use cases
⏳ Project Duration: 90 hours (Small)
📈 Difficulty: Easy
👥 Mentor(s): Diego Sampaio, Guilherme Gazzo, Tasso Evangelista, Sing Li
💬 Description: This can possibly be the most challenging (and rewarding) project this season, for the "right" candidate. You will be combing through the massive Rocket.Chat core code base and mapping the critical parts that can be mocked and then implement the injectables for unit testing.
Rocket.Chat is an open source nodeJS based, highly scalable production server that is used by millions daily. Designing and implementing mocks, injectables, and unit testing framework for this sort of scaled server is currently considered pioneering work in open source. Are you up for the challenge?
💪 Desired Skills: Knowledge of TypeScript, JavaScript, MongoDB, MicroServices, Dependency Injection, and Unit Testing. Must be passionate about creating test harnesses for modern "impossibly large" real-time server systems.
🎯 Goals/Deliverables:
- Map the critical parts, like collections and services.
- Refactor parts of the codebase that are not injectable yet.
- Create an api/approach to generate mocks for the injectable parts.
- Create a guide for the developers to use the mocks in the unit tests.
- Create a few examples of unit tests using the mocks.
⏳ Project Duration: 175 hours (Medium)
📈 Difficulty: Hard
👥 Mentor(s): Tasso Evangelista, Guilherme Gazzo, Douglas Fabris
💬 Description: Rewrite the Fuselage components using tha tamagui library. With the objective of improving the performance and the maintainability of the components. But also allowing the use of the components in different platforms, like React Native.
💪 Desired Skills: Knowledge of TypeScript, JavaScript, React, React Native, and Rocket.Chat Fuselage.
🎯 Goals/Deliverables:
- Rewrite the components using the tamagui library.(At least the most used ones)
- Run some of the old projects (rocketchat/livechat/onboarding/uikitplayground) using the new components.
⏳ Project Duration: 175 hours (Medium)
📈 Difficulty: Hard
👥 Mentor(s): Douglas Fabris, Guilherme Gazzo, Tasso Evangelista
💬 Description:
Implement the translations in the UIKit Playground, allowing the user to change the language and see the components in different languages, helping to handle the dictionaries and the translations in the UIKit.
Transform all the project in to a scaffold to be used as rocketchat app.
💪 Desired Skills: Knowledge of TypeScript, JavaScript, React, and Rocket.Chat UIKit.
🎯 Goals/Deliverables:
- Create a new section in the UIKit Playground to handle the translations.
- Implement the translations in the UIKit Playground.
- Implement code generation for the UIKit Playground to be used as a scaffold for new Rocket.chat apps.
⏳ Project Duration: 175 hours (Medium)
📈 Difficulty: Intermediate
👥 Mentor(s): Rodrigo Nascimento, Guilherme Gazzo, Diego Sampaio,
💬 Description: Based on the codebase and typescript definitions, generate the openapi and swagger files.
💪 Desired Skills: Knowledge of TypeScript, JavaScript, and Rocket.Chat API.
🎯 Goals/Deliverables:
- Generate the openapi and swagger files, based on the codebase and typescript definitions.
- Provide an automated way to keep the documentation updated.
- Version the documentation based on the Rocket.Chat version.
⏳ Project Duration: 175 hours (Medium)
📈 Difficulty: Intermediate
👥 Mentor(s): Mustafa Hasan Khan
💬 Description: Create a Rocket.Chat app that will write short code modules in C/C++, Java, Javascript, Typescript or Python based on specification supplied by the user. The app should leverage modern open source LLMs (Mistral, CodeLlama, WizardCode, Llama2, Phi, and so on) to write the code. The user must be able to quickly reject and ask for a new variation of the code if desired; the user should also be able to augment/fine-tune the system prompt for more precise code generation (designing an intuitive Ux here can be tricky). Minor editing of generated code should be allowed and easy to make. Finally accepted generated code should be available to be injected into the current channel as a syntax highlighted message, shared to external application, or added to Github (with the associated credentials configured) as a pull request.
💪 Desired Skills: Rocket.Chat App development. LLM prompt design/engineering.
🎯 Goals/Deliverables: A working Rocket.Chat App that can act as a programming assistant to any developer user of Rocket.Chat.
⏳ Project Duration: 90 hours (Small)
📈 Difficulty: Easy
👥 Mentor(s): Shubham Bhardwaj, Sing Li
💬 Description: Create a Rocket.Chat app that will add emoji to an old-school plain text message. The app should leverage modern open source LLMs (Mistral, Llama2, Phi, and so on) to inject the emojis. User should be able to adjust the level of embellishment, and should be able to ask for a re-do if needed. User should be able to make some small edits after emjois are added. The finally accepted message should be available to be injected into the current channel, shared to external application, or copied to system clipboard.
💪 Desired Skills: Rocket.Chat App development. LLM prompt design/engineering.
🎯 Goals/Deliverables: A Rocket.Chat App that can turn any boring old-school text messages into sensitive modern emojified masterpieces.
⏳ Project Duration: 90 hours (Small)
📈 Difficulty: Easy
👥 Mentor(s): Debdut Chakraborty
💬 Description: A simple client in VSCode to have conversations with your team mates through ROcket.Chat. The goal is for developers to be able to communicate better, which means it will have to provide some simple but different featureset than a normal client.
💪 Desired Skills: Knowledge of VSCode extension building, TypeScript, Rocket.Chat API.
🎯 Goals/Deliverables: Through the extension, we should be able to
- log in to individual server
- converse with colleagues
- share code lines directly from the editor (blame links, line links etc) and open them as such
- able to collaborate with a team member with ease (member picked from rocket.chat contact list)
⏳ Project Duration: 175 hours (Medium)
📈 Difficulty: Hard
👥Mentor(s): Devanshu Sharma (@Dnouv), Douglas Gubert
💬Description: Create a Rocket.Chat app that acts as a Smart Scheduling Assistant. The app should be able to understand the context of a conversation, suggest meeting times, send calendar invites, or set reminders based on the chat content. The app should be configurable via the App's settings, allowing customization of the AI's understanding and response generation. The code should include at least two concrete examples of scheduling scenarios.
💪Desired Skills: Rocket.Chat App development. LLM prompt development, including function calling (tools pattern). Experience with calendar APIs (specifically Google Calendar API).
🎯Goals/Deliverables: A flexible Smart Scheduling Assistant, fronting Google Calendar, that can understand and respond to scheduling requests in any conversation on Rocket.Chat.
⏳Project Duration: 175 hours (Medium)
📈 Difficulty: Intermediate
👥 Mentor(s): Douglas Gubert, Devanshu Sharma (@Dnouv)
💬 Description: This Rocket.Chat app leverages modern open source LLMs (Mistral, Llama2, Phi, and so on) to help generate newsletters for special interest groups and/or teams operating on a Rocket.Chat server. The newsletter author should be able to supply raw content to the AI generator and have perfectly phrased and formatted newsletter generated. The app should allow for the immediate or scheduled publication of the resulting newsletter to either a team, subset of the server's user, or all of the server's users. The app should also allow for emailing those who prefers to receive the newsletter via email. Ideally the app should maintain a list of dynamically changing newsletter subscribers.
💪 Desired Skills: Rocket.Chat App development. LLM prompt design/engineering.
🎯 Goals/Deliverables: A working Rocket.Chat App that can generate newsletter for a user group or team.
⏳ Project Duration: 90 hours (Small)
📈 Difficulty: Easy