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week 12 update by Om Santosh Suneri (#385)
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‎src/constants/MarkdownFiles/posts/2025-08-24-gsoc-25-omsuneri-week12.md‎

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---
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title: "GSoC’25 Week 12 Update by Om Santosh Suneri"
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excerpt: "AI-powered Debugger for Music Blocks"
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category: "DEVELOPER NEWS"
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date: "2025-08-24"
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slug: "2025-08-24-gsoc-25-omsuneri-week12"
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author: "@/constants/MarkdownFiles/authors/om-santosh-suneri.md"
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tags: "gsoc25,sugarlabs,week12,Debugger,AI,Music Blocks,Final Submission"
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image: "assets/Images/GSOC.png"
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---
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<!-- markdownlint-disable -->
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# Week 12 Progress Report by Om Santosh Suneri
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**Project:** [AI-powered Debugger for Music Blocks](https://github.com/omsuneri/AI-powered-Debugger-for-Music-Blocks)
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**Mentors:** [Walter Bender](https://github.com/walterbender/) [Sumit Srivastava](https://github.com/sum2it)
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**Assisting Mentors:** [Devin Ulibarri](https://github.com/pikurasa/)
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**Reporting Period:** 2025-08-21 - 2025-08-24
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---
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## Goal for This Week
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The **primary objective** for this final week of Google Summer of Code 2025 was to **refactor and modularize the backend FastAPI server**, enabling it to operate **independently from the Streamlit frontend**. Additionally, I aimed to make the project **production-ready by deploying it on an AWS EC2 instance using systemd**, allowing continuous availability of the service.
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Alongside the deployment, I also worked on **documenting the complete contributor and user experience**, ensuring that **future contributors and users can easily get started** with the AI Debugger system.
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---
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## This Week’s Achievements
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### Backend Independence from Streamlit
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One of the **most important milestones** of this week was separating the **FastAPI backend** from the **Streamlit app**. Previously, the backend was tightly coupled with the Streamlit interface, limiting flexibility. I restructured the repository and added an **independent `api.py` file** that runs **Uvicorn as a FastAPI app**, making it easier to scale, test, and deploy.
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```bash
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# Now the backend can be launched directly with:
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python -m uvicorn app.api:app --host 0.0.0.0 --port 8000
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```
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This approach aligns with production-grade practices and allows the **Streamlit app and FastAPI backend to scale independently**.
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### Production Deployment on AWS EC2 with systemd
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To ensure the backend could **serve users 24/7**, I set up a **dedicated EC2 instance** on AWS and deployed the backend using a `systemd` service.
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Here’s a breakdown of the finalized configuration:
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```ini
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[Unit]
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Description=Debugger for Music Blocks - FastAPI backend
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After=network.target
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[Service]
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User=ubuntu
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WorkingDirectory=/home/ubuntu/AI-powered-Debugger-for-Music-Blocks
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ExecStart=/home/ubuntu/AI-powered-Debugger-for-Music-Blocks/venv/bin/python -m uvicorn app.api:app --host 0.0.0.0 --port 8000
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Restart=always
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RestartSec=5
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Environment=PYTHONUNBUFFERED=1
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[Install]
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WantedBy=multi-user.target
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```
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**Key Highlights:**
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* `ExecStart` runs Uvicorn directly from the virtual environment, ensuring environment consistency.
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* `Restart=always` allows **automatic recovery** in case of backend crashes.
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* Using `systemctl`, I enabled and started the service:
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```bash
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sudo systemctl daemon-reload
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sudo systemctl enable debugger.service
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sudo systemctl start debugger.service
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```
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This ensures the backend remains **persistent and robust**, especially under real-world usage.
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### Contributor Documentation
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To make the project **accessible for new developers**, I authored the **AI-powered Debugger Widget - Contributor Guide**, which outlines the full stack — from the frontend widget integration to backend architecture.
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Some key highlights:
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* **Architecture Overview**:
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<a href=""><img src="https://i.ibb.co/CK8qXhfm/Screenshot-2025-08-22-at-12-34-44-AM.png" alt="Debugger Architecture"></a>
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* **API Interaction Sample**:
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```js
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fetch("http://13.49.246.243:8000/analyze", {
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method: "POST",
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headers: { "Content-Type": "application/json" },
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body: JSON.stringify({
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code: projectData,
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prompt: message,
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history: history,
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prompt_count: this.promptCount
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})
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});
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```
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📎 [Contributor Guide on GitHub](https://github.com/omsuneri/musicblocks/blob/Debugger-docs/js/widgets/aidebugger-guide.md)
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### User Guide & Demo Video
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To assist end-users, especially **students, teachers, and parents**, I published a **visually engaging User Guide** along with a demo video:
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<a href=""><img src="https://i.ibb.co/93HCW8hC/Screenshot-2025-08-22-at-12-45-48-AM.png" alt="AI-Powered Debugger Widget Demo"/></a>
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**🎥 [Click to Watch the Demo Video](https://www.youtube.com/watch?v=G-NfDo_A5PM)**
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This guide explains:
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* How to drag and use the AI Debugger widget
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* Example questions to ask the AI
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* How the AI assistant explains errors and suggests fixes
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📘 [AI-Powered Debugger Widget Guide](https://github.com/omsuneri/musicblocks/blob/Debugger-docs/AI-Debugger-widget-guide.md)
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---
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### Why It Matters
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This week's work marks a **significant transition from development to deployment**. By **decoupling the backend**, setting up **system-level service management**, and providing **comprehensive documentation**, the project is now **fully production-ready**.
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This effort makes the **AI Debugger more scalable**, **developer-friendly**, and **accessible to educators and learners** across the Sugar Labs community. Now, **Music Blocks users can rely on a stable, intelligent assistant** to help them debug their musical creations in real time.
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---
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### Final Thoughts
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As this marks the **final official week of Google Summer of Code 2025**, I want to take a moment to reflect on this incredible journey.
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Working on this project has not only sharpened my technical skills in **FastAPI**, **Streamlit**, **systemd**, **deployment pipelines**, and **full-stack architecture**, but also introduced me to the **open-source world** in the most collaborative way possible. I’m **deeply grateful** to my mentors and the Sugar Labs community for their continuous support and guidance.
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Building the AI-powered Debugger has been **one of the most fulfilling experiences** of my development journey so far. The ability to contribute to something that helps kids **learn music and programming more easily** makes me feel proud and inspired for future contributions.
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---
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## Resources & References
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* **Backend Repository**: [AI Debugger](https://github.com/omsuneri/AI-powered-Debugger-for-Music-Blocks)
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* **Frontend Widget Code**: [Music Blocks Repository](https://github.com/omsuneri/musicblocks/blob/Debugger-docs/js/widgets/aidebugger.js)
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* **Documentation**: [Contributor Guide](https://github.com/omsuneri/musicblocks/blob/Debugger-docs/js/widgets/aidebugger-guide.md) | [User Guide](https://github.com/omsuneri/musicblocks/blob/Debugger-docs/AI-Debugger-widget-guide.md)
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* **Demo Video**: [Watch on YouTube](https://www.youtube.com/watch?v=G-NfDo_A5PM)
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---
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## Acknowledgments
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Huge thanks to my mentors **Walter Bender**, **Sumit Srivastava**, and **Devin Ulibarri** for their mentorship, trust, and encouragement throughout the summer.
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Thanks also to the **Sugar Labs community** for welcoming me and providing constant feedback and motivation.
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I look forward to staying active in this community, contributing more, and supporting new learners through the tools we’ve built together.
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---
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*Made with ❤️ for Music, Open Source, and Learning.*
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