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Author: amannaik247

src/constants/MarkdownFiles/posts/2025-06-08-dmp-25-AmanNaik-week01.md

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+---
+title: "DMP ’25 Week 01 Update by Aman Naik"
+excerpt: "This week's focus was exploring the write-activity codebase, finding appropriate grammar correction models & understanding Abiword documentations."
+category: "DEVELOPER NEWS"
+date: "2025-06-09"
+slug: "dmp-25-AmanNaik-week01"
+author: "Aman Naik"
+description: "Member and DMP'25 Contributor at SugarLabs"
+tags: "dmp25,writeactivity,write,sugarlabs,week01,amannaik247"
+image: "assets/Images/c4gt_DMP.png"
+---
+
+<!-- markdownlint-disable -->
+
+# Week 01 Progress Report by Aman Naik
+
+**Project:** [Add an AI-assistant to the Write Activity](https://github.com/sugarlabs/write-activity/issues/52)  
+**Mentors:** [Walter Bender](https://github.com/walterbender), [Ibiam Chihurumnaya](https://github.com/chimosky). 
+**Assisting Mentors:** [Devin Ulibarri](https://github.com/pikurasa)  
+**Reporting Period:** 2025-06-02 - 2025-06-08  
+
+---
+
+## Goals for This Week
+
+- **Goal 1:** Understand write activity's codebase.
+- **Goal 2:** Explore pertinent grammar correction models for real time grammar correction
+- **Goal 3:** Understand the [Abiword](https://github.com/AbiWord) word-processor documentation
+
+---
+
+## This Week’s Achievements
+
+1. **Understood the activity's codebase**  
+   - Gained a clear understanding of the overall structure and logic of the Write activity's codebase.
+   - This includes identifying key components, data flow, and how the Abiword processor is leveraged for this activity.
+2. **Explored pertinent grammar correction models**  
+   - Shortlisted grammar correction models suitable for real time grammar correction and can be used with an open source software.
+   - Created API endpoints using Hugging Face spaces for quick testing in sugar.
+
+3. **Understood the Abiword processor**  
+   - Abiword is an open source word processor, which is leveraged by the write activity.
+   - It has a parser called 'link-grammar' that was recently developed, which might be useful for grammar correction as well.
+
+---
+
+## Challenges & How I Overcame Them
+
+- **Challenge:** Difficulty in finding reliable grammar correction models on hugging face which can also be compatible open source software.  
+**Solution:** Found link-grammar that could be an option for reliable grammar correction feature. Also, found some hugging face models(relevant license) after rigorously searching. 
+
+- **Challenge:** Testing hugging face models with no inference points and testing them inside Sugar.  
+**Solution:** Most Hugging Face models can’t be installed directly in Sugar because they require heavy dependencies like Torch and Transformers, which increase memory usage in a virtual machine. Therefore, I used hugging face spaces and ran the models there, which also provides API endpoints for quick testing inside Sugar.
+
+---
+
+## Key Learnings
+
+- Gained a solid understanding of the Write activity's code structure and how it integrates the Abiword processor.
+- Explored lightweight, open-source grammar correction models and successfully tested them using Hugging Face Spaces via API endpoints.
+- Discovered that Abiword’s link-grammar parser might be leveraged for native grammar correction within the activity.
+
+---
+
+## Next Week’s Roadmap
+
+- Finalise a grammar correction model and fine tune it if needed
+- Create a FastAPI endpoint and upload the selected model on AWS for testing
+- Integrate grammar correction into write-activity
+- Explore better spelling correction models
+
+---
+
+## Acknowledgments
+
+Thank you to my mentors, the Sugar Labs community, and fellow contributors for your continued guidance and support!
+
+---
+
+## Connect with Me
+
+- GitHub: [@amannaik247](https://github.com/amannaik247)
+- Gmail: [[email protected]](mailto:[email protected])
+- LinkedIn: [Aman Naik](https://www.linkedin.com/in/aman-naik/)
+
+---