Hy @cybette,
Im Shehrbano Ali an Outreachy applicant for an LLM project. Im sorry I got a lil bit late in catching up with u guys, but now I am fully N completely available to do tasks. can u please assign me any issue. bcz I haven’t done even one, I really want to contribute. kindly give me a chance.
Hy @jflory7,
I’m Shehrbano Ali, an Outreachy applicant for an LLM project. I’m so sorry I got a little late in catching up with you guys, but now I am completely available to do tasks. Can you please assign me any issues because I haven’t done any yet and I’m so worried, I really want to contribute. I’ve completed the pre requisite issues. As of now only #123 issues are published. Kindly give me a chance for the next one.
@jflory7 & @cybette:
ISSUE #109, #110, AND #111 are currently on hold. Kindly assign me one of them.
Hello everyone,
My name is Aman, and I’m an Outreachy applicant for the “Develop a SLM/LLM using RamaLama RAG based off Fedora RPM Packaging Guidelines” project.
Open Source Journey:
My open source journey began in May 2025 with Meshery, where I explored service mesh technologies, followed by contributions to RISC-V projects. Currently, I am contributing to Oppia and other ML projects. These experiences have given me practical exposure to real-world projects; for example, I learned GitHub Actions while contributing to Meshery.
Why Fedora:
I am a Linux enthusiast and currently use Linux Mint, which has strengthened my interest in open-source software and communities. I am interested in Fedora as it provides an opportunity to contribute to a meaningful open-source project, collaborate with an active community, and gain real-world development experience.
I also want to give back to the Linux and open-source community, as I have personally benefited a lot from using Linux and open-source tools throughout my learning journey.
Why RamaLama/AI project:
I’m excited about the RamaLama RAG project because it focuses on applying AI and large language models to real-world problems. This is an area I’m currently working on and plan to explore further through reinforcement learning. I have built projects like Multimodal RAG Chatbot, a high-performance RAG system that allows users to interact with PDF documents, including images and charts, giving me hands-on experience with multimodal AI and LLMs.
My Goals:
My goal is to understand how RAG systems can be applied to real-world problems like RPM packaging and improve the quality of their responses. I also want to strengthen my understanding of LLM behavior and experiment with ways to make outputs more accurate and consistent while contributing meaningful improvements to the project.
Just for fun:
If I could instantly become a world-class expert, it would be leadership, because it involves guiding teams, making decisions, and bringing out the best in people.
Looking forward to contributing and learning alongside everyone here!
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@shehrbanoali6 Thank you for your intro post. However, this is not the forum to ask about the issue assignments. Please refer to my comments to you in Forgejo about what you need to do for the assignments.
We are at the first week of the application period. There’s ~3 more weeks left, and we will be creating more issues. So please don’t panic, there will be opportunities available within this period. 
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Alright Carol, I got it. Thanks you for informing me.
Hello Mentors, Outreachy applicants and the Fedora team at large.
My name is Farhana, and I am a Junior Data Scientist based in Nairobi, Kenya. I am thrilled to be part of this Outreachy cohort and to contribute to the RamaLama RAG SLM/LLM project #1.
Open Source journey:
I am a self-taught learner on online platforms, where I have completed coursework in Data Analysis with SQL, Data Science and Machine Learning in Python via DataCamp, and foundational cloud architecture through IBM Cloud Computing Fundamentals and AWS Cloud Practitioner Essentials.
My experience with open source has primarily been as a user of powerful libraries like scikit-learn, pandas, Numpy, and Plotly Dash to build data-driven solutions. While I have used these tools extensively during my Applied Data Science internship at WorldQuant University, this is my first time contributing directly to a major open-source system like Fedora. I am eager to transition from a user to a contributor.
Why:
I chose Fedora because is a platform where global, diverse community pushes the boundaries of open-source operating systems. I was specifically drawn to the RamaLama/AI project because it perfectly aligns with my background and experience in developing and deploying AI/ML solutions. Having worked on end-to-end projects involving predictive modeling and API development, the prospect of building a RAG-based system using Small Language Models is incredibly exciting to me. I am particularly interested in how we can make AI more accessible and efficient through localized infrastructure.
My goals:
My number one goal is to learn how to bridge the gap between Data Science and open-source infrastructure. While I have certifications in AWS and IBM Cloud Computing, I want to gain hands-on experience in how a global community collaboratively maintains and scales AI tools within a Linux distribution.
I hope to leave this cohort with a deep understanding of the Fedora packaging ecosystem and how to contribute and generate high-quality code that meets the community’s standards.
For fun:
If I could instantly become a world-class expert in any one non-technical skill, it would be archery. I’ve always admired the focus, patience, and precision it requires, qualities that are also very helpful when debugging complex machine learning models. I look forward to working with you all and learning from the mentors and participants.
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Dear mentors and Fellow Open Source contributors, Good day! I’m Francois Gonothi Toure, an Outreachy May 2026 round contributor at the Fedora project that feeds the aura of Open Source (OS) software to the world.
I have been involved in OS for quite a while now and have had involvement with communities at the Oppia Foundation, Open Robotics, JdeRobot, OpenStack, and now the Fedora project.
Upon the approval of my Outreachy initial application, I started exploring the available projects and was particularly drawn to the Fedora project #1 (the RamaLama AI project) on the Outreachy selected projects page due to the high impact it has on simplifying RAG-related work, but most importantly, it seemed to be the best fit for me as a final-term Master’s in CS student, specializing in IA, at UQAM, and an upcoming PhD in Computer Engineering student at Polytechnique Montréal. It’s the project that interests me the most in this Outreachy cycle, and that best aligns with my current skillset and my experience. I hope to spend my next summer vacation working on this alongside the mentors and learning a lot from them prior to my PhD studies, and become a Fedoraians for the rest of my OS journey.
Although the end goal is to make the Outreachy interns list, to me, there is pride in giving back to the community with what you have or can do best. At the end of this contribution period, I would like to pat my back for the quality contribution that I may have made to Fedora and how this will benefit others. Some day, looking back, I can at least relate it to my kids and encourage them to give back through quality community contribution. My hope is to learn from the mentors as an intern during the summer, as I will be free from school and preparing for my PhD transition, and most interestingly, become a lifelong valued member of the Fedora community.
If I were to pick the one non-technical skill to become a world-class expert in, it would be cooking multicultural gastronomic dishes because of the algorithmic process that lies behind various cooking recipes. In fact, it’s the one thing that I like doing when I am off my PC and away from any tech-related work.
Happy OS contribution to all of us, and I hope we all find purpose in free software development for the betterment of the world.
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That’s amazing, I feel that cooking gastronomic dishes is totally about feel and a reciprocity between the cook and the cooked - imagine if we mixed our ‘opposite’ approaches!
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Hi everyone! I’m Varsha, an Outreachy 2026 applicant.
My Open Source Journey:
I have prior experience contributing to open source through GirlScript Summer of Code, where I worked on improving user-facing features using React and JavaScript. I contributed to enhancing a jobs platform by implementing real-time search and advanced filtering to improve usability and accessibility.
Alongside that, I’ve worked as an AI Engineer Intern, where I focused on building and testing components in an AI-driven logistics workflow. A key part of my work involved designing edge-case tests to improve the accuracy and stability of LLM outputs.
My “Why”:
I’m particularly interested in systems that make AI more reliable and usable in real-world applications. From my experience working with LLMs, I’ve seen how unpredictable and difficult to manage they can be, so the idea of creating structured, reproducible workflows around them is something I find very compelling.
My Goals:
Over the next few weeks, I want to understand how systems like RamaLama abstract complexity while still giving control over model behavior, and how such setups can be used to build more dependable and consistent LLM driven workflows in practice.
Just for fun:
If I could instantly become great at a non-technical skill, it would be football. I really enjoy the game and the energy around it, both playing and watching, and the discipline that goes into training. I’m also quite observant and interested in psychology, especially how people think and behave in different situations. Understanding that layer of reasoning and human behavior is something I find very interesting.
Looking forward to learning and contributing with everyone here!
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Now I’m curious what that ‘mixed approach’ dish would taste like 
might be a fun challenge to try one day!
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Hello Emmanuel here,
Your Open Source journey:
I’ve contributed to open source a couple of times before, mainly around Python-based projects. I’m still learning a lot, but working in real projects has helped me understand collaboration, code reviews, and how open source communities operate.
Why I chose Ramalama
I chose Fedora and the RamaLama/AI project because I’m really interested in how AI systems are built and orchestrated behind the scenes. The idea of working on something that interacts with AI models at scale caught my attention.
My goals
The main thing I hope to learn in the next few weeks is how AI systems and infrastructure work in real-world environments, not just using models, but understanding the systems around them.
And for fun?
If I could instantly become world-class at a non-technical skill, it would be communication and team collaboration. I think being able to work and communicate effectively with people is a superpower in any field.
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Hi, I’m Omar Agiez, an Applied Statistics graduate and a Python developer. I’m interested in Python open-source projects. I worked as a session lead at Udacity, teaching CS. Last year, I won a GenAI hackathon sponsored by AWS in North Africa.
- My Open Source journey:
I’ve been actively involved in open source for 1.5 years now. I’ve contributed to projects like Wikimedia’s Scribe-Data and worked with a team on building the i18n-check Python package, which is published on PyPI. Through these experiences, I’ve worked on CI/CD pipelines, testing, and writing production-ready Python code. Open source has been a big part of how I’ve grown as an engineer, especially learning how to collaborate across distributed teams. - My “Why”:
I chose Fedora because it sits at the intersection of real-world impact and strong open-source values. The scale at which Fedora operates and its role in the Linux ecosystem makes it exciting to contribute to.
The RamaLama/AI project specifically caught my attention because it combines two areas I’m deeply interested in: machine learning and systems-level problem solving. I’m particularly excited about applying ML in a practical infrastructure context, not just building models but integrating them into real workflows. - My goals:
The number one thing I want to gain from this experience is a deeper understanding of how large-scale open-source systems are designed and maintained especially within Fedora. I also want to improve my ability to contribute code that is not just functional, but maintainable, well-tested, and aligned with community standards. - Just for fun:
If I could instantly master a non-technical skill, it would be communication specifically the ability to explain complex ideas in a simple and engaging way. I think this skill is incredibly powerful because it helps bridge gaps between people with different backgrounds, making knowledge more accessible. Whether in teaching, writing, or collaborating in open source, being able to communicate clearly can have a huge impact.
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Hi everyone, my name is Jamillah Bello.
My Open Source Journey
My current level of experience with open source software cuts across different areas. More often than not, I don’t even realise they’re OSS until I do some research on them. I’ll start with Linux, I dual-booted my system with Ubuntu for 3 years until I switched to Fedora during a previous Fedora Outreachy project I contributed to. Then i switched to dual-booting my windows OS with Kali Linux recently.
In terms of media, I make use of OBS Studio for screen recording and VLC Media Player for watching videos. Nginx and Apache are always my go-to web servers, with Nginx taking the lead, and Apache only looking good to me when it’s specifically required. I’m pretty sure there are other open source tools I use that I’m not aware of, so I won’t go too deep into that so I don’t end up typing too much 
My Why
I chose Fedora because of curiosity 
. That’s what drew me in the first time I got interested in it and attempted the DEI project for my previous Outreachy contribution. I chose this particular project because I’ve recently been getting into AI and how intelligent systems are built.
A friend and I are building a health and safety app to give Nigerians access to verified healthcare safety information and incident reports. The project relies heavily on APIs and AI, we’re integrating an AI system that ensures media information uploaded to the platform are real and not AI generated, to reduce the chances of users spreading panic with fake content, and I had to do a lot of research to carry out my tasks. In the process, my interest was really piqued. That combined with the fact that i’ve been looking into RAG and how AI can be used to simplify Cloud operations, contributing to this seems to just make sense.
My Goals
My goal for this Outreachy cohort is to leave better than I started. The number one thing I hope to take away from these next few weeks is knowledge and a hunger for more. I want to learn new things, improve my technical skills, gain practical experience and understand AI systems better, contribute meaningfully, and get hands-on experience.
For my non-technical skill, I would choose to be great at karate. I’d like to be a skilled martial artist, mainly for self-defense. I’ve been in situations where it would have come in handy. I recently started taking taekwondo classes and it’s been great. Aside from the main reason I started, it has really helped my mental health. I feel more centred and at peace while training. But that’s just one part, I’d love to become an MMA expert overall 
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Hey folks! 
I always enjoy reading through the introductions and seeing the energy y’all are bringing to the contribution phase.
In case you missed it or didn’t see the calendar invite, we hosted an onboarding session yesterday called Demystifying Open Source, Free Software, & 46 Years of a Legacy.
We recorded the whole presentation and Q&A! If you are new to Open Source, or if you just want to get a better understanding of the “why” behind the Fedora Project, I recommend checking out the replay. I introduce FOSS history, the Four Freedoms, and some practical career advice on how to find your way in the tech industry.
Watch the replay here:
Getting started in open source can feel a bit overwhelming at first, but remember that every single contributor started exactly where you are right now. Keep asking questions, lean into the hard stuff, and keep connecting with the community.
Good luck with the rest of your contributions! We are rooting for you. 
4 Likes
Hello, @jflory7. What an interestingly instructive session it’s been. As I keep watching it right now, I would like to know if there is a form to fill out or a newsletter to subscribe to for upcoming sessions. I personally missed this one because I wasn’t aware of it.
ThankYou @jflory7 , would be happy to attend the upcoming sessions. Is there anything I should do to get the notifications for the upcoming sessions?
Hello everyone,
My name is Ibrahim, and I’m excited to be part of the Fedora community.
I am at an early stage in my open source journey. Most of my experience has been through self-learning and personal projects, working with Python and Django, and exploring backend concepts, I have built several projects amongst which are Multi-tenancy e-commerce and inventory management system API and a web based learning management system to help young people in the tech ecosystem, I have not made many open source contributions yet, but I have been actively building my skills and preparing to contribute meaningfully.
I chose Fedora because of its strong open source culture and emphasis on collaboration. The RamaLama RAG SLM/LLM project stood out to me because it combines AI with real-world systems. I am particularly interested in how structured knowledge (like Fedora RPM packaging guidelines) can be transformed into intelligent systems that assist developers. That intersection of AI and practical tooling is something I want to deeply understand.
My main goal is to learn how to contribute effectively to a real open source AI project, especially understanding how LLMs and RAG systems are designed, trained, and integrated into useful tools.
If I could instantly master one non-technical skill, it would be storytelling. I believe storytelling is a powerful way to simplify complex ideas and inspire people, and it’s a skill I want to develop alongside my technical growth.
Looking forward to learning, contributing, and growing with everyone here.
Thank you!
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Hi everyone,
I’m Akriti Sengar, an Outreachy 2026 applicant working on the project “Develop a SLM/LLM using Ramalama RAG based off Fedora RPM Packaging Guidelines.”
1. My Open Source journey:
I’m relatively new to open source. I’ve explored projects before, but this is the first time I’m actively contributing and trying to understand how things work in a real community setting.
2. My “Why”:
I chose Fedora because I really liked how welcoming and structured the community is. The Ramalama/AI project especially caught my interest because I’m currently pursuing AI/ML and I’m curious about how LLMs can be built and applied in real-world use cases.
3. My goals:
My main goal is to learn how to actually contribute meaningfully to an open source project—understanding the workflow, improving my technical skills, and becoming more confident while collaborating with others.
4. Just for fun:
If I could instantly master a non-technical skill, it would be writing (especially emotional or expressive writing). I enjoy it a lot, and I’d love to get really good at conveying thoughts and feelings through words.
Looking forward to learning and contributing with everyone here!
1 Like
Hi everyone,
My name is Happiness Omale. I’m a data scientist and technical writer who enjoys breaking down complex technical concepts into simple explanations. I’ve also spent time doing community management and supporting tech communities, which is where my interest in open source collaboration really started to grow.
-
My Open Source Journey:
Most of my experience with open source so far has been through learning, writing, and sharing technical content about tools and technologies. I enjoy documenting things and helping others understand them more easily. -
My “Why”:
I chose to participate in Fedora because I admire how strong and collaborative the community is. The RamaLama project caught my attention because it combines two areas I’m interested in open source and AI. I’m curious about how RAG can be used to improve workflows. -
My Goals
The main thing I hope to gain from the next few weeks is a deeper understanding of how AI tools like RamaLama can be integrated into real open source projects. I’m also excited to learn more about Fedora and improve my open source. -
Just for Fun
I love to sleep.
Looking forward to learning from everyone here and contributing where I can!
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