From 88a3c891ea94b370f6ef9defefb1791303e8510a Mon Sep 17 00:00:00 2001 From: ac-mmi Date: Mon, 16 Jun 2025 12:45:34 +0530 Subject: [PATCH 1/4] DMP Week-2 Blog --- .../posts/dmp-25-AmanChadha-week02.md | 95 +++++++++++++++++++ 1 file changed, 95 insertions(+) create mode 100644 src/constants/MarkdownFiles/posts/dmp-25-AmanChadha-week02.md diff --git a/src/constants/MarkdownFiles/posts/dmp-25-AmanChadha-week02.md b/src/constants/MarkdownFiles/posts/dmp-25-AmanChadha-week02.md new file mode 100644 index 00000000..0960a0d2 --- /dev/null +++ b/src/constants/MarkdownFiles/posts/dmp-25-AmanChadha-week02.md @@ -0,0 +1,95 @@ +--- +title: "DMP ’25 Week 02 Update by Aman Chadha" +excerpt: "Enhancing RAG output with part-of-speech tagging and optimizing chunk granularity" +category: "DEVELOPER NEWS" +date: "2025-06-16" +slug: "dmp-25-aman-week02" +author: "Aman Chadha" +description: "DMP '25 Contributor working on retrieval-augmented generation for Music Blocks" +tags: "dmp25,musicblocks,rag,week02" +image: "assets/Images/c4gt_DMP.png" +--- + +# Week 02 Progress Report by Aman Chadha + +**Project:** [JS Internationalization with AI Translation Support](https://github.com/sugarlabs/musicblocks/pull/4459) + +**Mentors:** [Walter Bender](https://github.com/walterbender) + +**Reporting Period:** 2025-06-09 – 2025-06-16 + +--- + +## Goals for This Week + +- Refine the RAG model output format for improved downstream use. +- Implement part-of-speech tagging to enrich context awareness in RAG retrieval. +- Reduce chunk size for more precise retrieval based on mentor feedback. +- Begin testing the RAG model with real-world queries. + +--- + +## This Week’s Achievements + +1. **Enhanced RAG Output Format** + - Updated the RAG model to return results in a dictionary structure. + - Included part-of-speech information for each translation unit, enabling more nuanced context retrieval. + +2. **Chunk Optimization** + - Adjusted AST-based code chunking logic to include only 5 lines above and below the relevant translation call. + - This change was implemented based on feedback from mentor Walter during a sync-up meeting. + - The refined chunk size improves focus and reduces noise in context matching. + +3. **Initial Testing of RAG Model** + - Started testing the RAG system with real query samples from Music Blocks. + - Observed initial improvements in contextual relevance due to enriched metadata and refined chunks. + +--- + +## Challenges & How I Overcame Them + +- **Challenge:** Integrating part-of-speech tagging meaningfully into the RAG pipeline. + **Solution:** Created a structured dictionary-based output that includes the msgid, msgstr, pos, and source metadata for every entry. + +- **Challenge:** Deciding optimal chunk boundaries without losing semantic context. + **Solution:** Followed mentor advice to use 5-line windows above and below relevant code, then verified accuracy by manual testing. + +--- + +## Key Learnings + +- Better metadata, such as part-of-speech labels, can significantly improve the performance of retrieval-augmented models. +- Small refinements in chunk size and structure can lead to clearer, more actionable context. +- Collaborative iteration with mentor input is crucial in aligning technical decisions with practical outcomes. + +--- + +## Next Week’s Roadmap + +- Integrate the refined RAG model into the full translation flow in Music Blocks. +- Evaluate RAG accuracy with various translation strings, particularly ambiguous or reused ones. +- Continue improving the fallback logic for missing translations using AI suggestions. + +--- + +## Resources & References + +- **Music Blocks Repository:** [github.com/your-org/musicblocks](https://github.com/your-org/musicblocks) +- **Babel AST Docs:** https://babeljs.io/docs/en/babel-parser +- **Part-of-Speech Tagging (spaCy):** https://spacy.io/usage/linguistic-features#pos-tagging +- **RAG Model Concepts:** https://arxiv.org/abs/2005.11401 + +--- + +## Acknowledgments + +Thanks to my mentor Walter Bender for his continued feedback and suggestions to improve retrieval relevance and model usability. + +--- + +## Connect with Me + +- GitHub: [@aman-chadha](https://github.com/ac-mmi) +- Gmail: [aman.chadha.mmi@gmail.com](mailto:aman.chadha.mmi@gmail.com) + +--- From ed445b0c42a2554c40977a299f25b809614456b4 Mon Sep 17 00:00:00 2001 From: ac-mmi Date: Mon, 16 Jun 2025 16:04:46 +0530 Subject: [PATCH 2/4] DMP '25 Week 02 Update by Aman Chadha --- .../MarkdownFiles/authors/aman-chadha.md | 29 +++++++ .../posts/dmp-25-AmanChadha-week02.md | 81 +++++++++---------- 2 files changed, 69 insertions(+), 41 deletions(-) create mode 100644 src/constants/MarkdownFiles/authors/aman-chadha.md diff --git a/src/constants/MarkdownFiles/authors/aman-chadha.md b/src/constants/MarkdownFiles/authors/aman-chadha.md new file mode 100644 index 00000000..532b3bba --- /dev/null +++ b/src/constants/MarkdownFiles/authors/aman-chadha.md @@ -0,0 +1,29 @@ +--- +name: "Aman Chadha" +slug: "aman-chadha" +title: "DMP'25 Contributor" +organization: "SugarLabs" +description: "DMP'25 Contributor at SugarLabs" +avatar: "https://avatars.githubusercontent.com/u/79802170?v=4" +--- + + + +# About Aman Chadha + +I am a DMP 2025 contributor working with Sugar Labs on enhancing Music Blocks' internationalization system using AI-supported translation. I'm passionate about building intelligent systems, developer tools, and creative educational platforms that empower users across languages. + +## Experience + +- Contributor at Sugar Labs (DMP '25) + +## Current Projects + +- **JS Internationalization with AI Translation Support**: + Integrating a modern i18n workflow in Music Blocks and enhancing it with AI-powered fallback translations, context-aware retrieval, and part-of-speech–informed RAG models. + +## Connect with Me + +- **GitHub**: [@ac-mmi](https://github.com/ac-mmi) +- **Email**: [aman.chadha.mmi@gmail.com](mailto:aman.chadha.mmi@gmail.com) + diff --git a/src/constants/MarkdownFiles/posts/dmp-25-AmanChadha-week02.md b/src/constants/MarkdownFiles/posts/dmp-25-AmanChadha-week02.md index 0960a0d2..4d3533a5 100644 --- a/src/constants/MarkdownFiles/posts/dmp-25-AmanChadha-week02.md +++ b/src/constants/MarkdownFiles/posts/dmp-25-AmanChadha-week02.md @@ -1,89 +1,88 @@ --- -title: "DMP ’25 Week 02 Update by Aman Chadha" -excerpt: "Enhancing RAG output with part-of-speech tagging and optimizing chunk granularity" +title: "DMP '25 Week 02 Update by Aman Chadha" +excerpt: "Enhanced RAG output format with POS tagging and optimized code chunking for Music Blocks" category: "DEVELOPER NEWS" date: "2025-06-16" -slug: "dmp-25-aman-week02" -author: "Aman Chadha" -description: "DMP '25 Contributor working on retrieval-augmented generation for Music Blocks" -tags: "dmp25,musicblocks,rag,week02" +slug: "2025-06-16-dmp-25-aman-chadha-week02" +author: "@/constants/MarkdownFiles/authors/aman-chadha.md" +tags: "dmp25,sugarlabs,week02,aman-chadha" image: "assets/Images/c4gt_DMP.png" --- + + # Week 02 Progress Report by Aman Chadha **Project:** [JS Internationalization with AI Translation Support](https://github.com/sugarlabs/musicblocks/pull/4459) - -**Mentors:** [Walter Bender](https://github.com/walterbender) - -**Reporting Period:** 2025-06-09 – 2025-06-16 +**Mentors:** [Walter Bender](https://github.com/walterbender) +**Assisting Mentors:** *None this week* +**Reporting Period:** 2025-06-09 - 2025-06-16 --- ## Goals for This Week -- Refine the RAG model output format for improved downstream use. -- Implement part-of-speech tagging to enrich context awareness in RAG retrieval. -- Reduce chunk size for more precise retrieval based on mentor feedback. -- Begin testing the RAG model with real-world queries. +- **Refactor RAG model output** to a structured dictionary format that includes part-of-speech (POS) tagging. +- **Optimize AST-based chunking** by limiting code context to 5 lines above and below translation usage, per mentor feedback. +- **Begin functional testing** of the updated RAG pipeline on real-world translation queries. --- -## This Week’s Achievements +## This Week's Achievements -1. **Enhanced RAG Output Format** - - Updated the RAG model to return results in a dictionary structure. - - Included part-of-speech information for each translation unit, enabling more nuanced context retrieval. +1. **RAG Output Enhancement** + - Refactored the Retrieval-Augmented Generation model to return results as structured dictionaries. + - Each entry now includes `msgid`, `msgstr`, source metadata, and the dominant part of speech, improving retrieval relevance. -2. **Chunk Optimization** - - Adjusted AST-based code chunking logic to include only 5 lines above and below the relevant translation call. - - This change was implemented based on feedback from mentor Walter during a sync-up meeting. - - The refined chunk size improves focus and reduces noise in context matching. +2. **Code Chunking Optimization** + - Reduced each extracted code chunk to include only 5 lines above and below the relevant `msgid` usage. + - This improves retrieval precision and avoids irrelevant surrounding code. + - Implemented using Babel’s AST traversal logic. -3. **Initial Testing of RAG Model** - - Started testing the RAG system with real query samples from Music Blocks. - - Observed initial improvements in contextual relevance due to enriched metadata and refined chunks. +3. **Initial Model Testing** + - Started testing the RAG model using sample translation queries. + - Observed noticeable improvements in answer context relevance due to cleaner chunks and richer metadata. --- ## Challenges & How I Overcame Them -- **Challenge:** Integrating part-of-speech tagging meaningfully into the RAG pipeline. - **Solution:** Created a structured dictionary-based output that includes the msgid, msgstr, pos, and source metadata for every entry. +- **Challenge:** Integrating POS tagging meaningfully into the RAG data pipeline. + **Solution:** Designed a dictionary schema that includes the part-of-speech alongside translation metadata, and verified correctness using test entries. -- **Challenge:** Deciding optimal chunk boundaries without losing semantic context. - **Solution:** Followed mentor advice to use 5-line windows above and below relevant code, then verified accuracy by manual testing. +- **Challenge:** Tuning chunk granularity without losing contextual utility. + **Solution:** Followed mentor Walter’s advice to use fixed ±5 line windows, and manually verified semantic coherence of resulting chunks. --- ## Key Learnings -- Better metadata, such as part-of-speech labels, can significantly improve the performance of retrieval-augmented models. -- Small refinements in chunk size and structure can lead to clearer, more actionable context. -- Collaborative iteration with mentor input is crucial in aligning technical decisions with practical outcomes. +- Part-of-speech tagging can significantly improve the contextual strength of retrieved translations. +- Smaller, focused code chunks often result in better retrieval precision for RAG applications. +- Mentor feedback and collaborative iteration are key to refining both code structure and user outcomes. --- -## Next Week’s Roadmap +## Next Week's Roadmap -- Integrate the refined RAG model into the full translation flow in Music Blocks. -- Evaluate RAG accuracy with various translation strings, particularly ambiguous or reused ones. -- Continue improving the fallback logic for missing translations using AI suggestions. +- Integrate POS-tagged RAG responses into the full i18n fallback translation pipeline. +- Expand test coverage to include edge-case translations and re-used `msgid`s. +- Prepare an internal demo to show RAG-powered retrieval resolving contextually ambiguous translation strings. --- ## Resources & References -- **Music Blocks Repository:** [github.com/your-org/musicblocks](https://github.com/your-org/musicblocks) -- **Babel AST Docs:** https://babeljs.io/docs/en/babel-parser -- **Part-of-Speech Tagging (spaCy):** https://spacy.io/usage/linguistic-features#pos-tagging -- **RAG Model Concepts:** https://arxiv.org/abs/2005.11401 +- **Repository:** [github.com/sugarlabs/musicblocks](https://github.com/sugarlabs/musicblocks) +- **RAG Concepts:** [arxiv.org/abs/2005.11401](https://arxiv.org/abs/2005.11401) +- **Babel Parser Docs:** [babeljs.io/docs/en/babel-parser](https://babeljs.io/docs/en/babel-parser) +- **spaCy POS Tagging:** [spacy.io/usage/linguistic-features#pos-tagging](https://spacy.io/usage/linguistic-features#pos-tagging) --- ## Acknowledgments -Thanks to my mentor Walter Bender for his continued feedback and suggestions to improve retrieval relevance and model usability. +Thanks to my mentor Walter Bender for his guidance on optimizing chunking strategy and enriching the retrieval logic with linguistic features. --- From 34871d19ae725f20dae1bb2706c5d3b2d47d356f Mon Sep 17 00:00:00 2001 From: ac-mmi Date: Mon, 23 Jun 2025 16:06:11 +0530 Subject: [PATCH 3/4] DMP Week-3 Blog --- .../posts/dmp-25-AmanChadha-week03.md | 88 +++++++++++++++++++ 1 file changed, 88 insertions(+) create mode 100644 src/constants/MarkdownFiles/posts/dmp-25-AmanChadha-week03.md diff --git a/src/constants/MarkdownFiles/posts/dmp-25-AmanChadha-week03.md b/src/constants/MarkdownFiles/posts/dmp-25-AmanChadha-week03.md new file mode 100644 index 00000000..8debe535 --- /dev/null +++ b/src/constants/MarkdownFiles/posts/dmp-25-AmanChadha-week03.md @@ -0,0 +1,88 @@ +--- +title: "DMP '25 Week 03 Update by Aman Chadha" +excerpt: "Translated RAG-generated context strings, initiated batch processing, and planned for automated context regeneration" +category: "DEVELOPER NEWS" +date: "2025-06-23" +slug: "2025-06-23-dmp-25-aman-chadha-week03" +author: "@/constants/MarkdownFiles/authors/aman-chadha.md" +tags: "dmp25,sugarlabs,week03,aman-chadha" +image: "assets/Images/c4gt_DMP.png" +--- + + + +# Week 03 Progress Report by Aman Chadha + +**Project:** [JS Internationalization with AI Translation Support](https://github.com/sugarlabs/musicblocks/pull/4459) +**Mentors:** [Walter Bender](https://github.com/walterbender), [Devin Ulibarri](https://github.com/devinulibarri) +**Assisting Mentors:** *None this week* +**Reporting Period:** 2025-06-17 – 2025-06-23 + +--- + +## Goals for This Week + +- Translate a sample set of RAG-generated context strings using AI-powered tools. +- Share Japanese translation variants (Kana and Kanji) with mentors for review. +- Begin building a batch-processing workflow to generate context for all 1535 msgid entries in the .po files. +- Plan an update pipeline to regenerate context for newly added or reused translation strings automatically. + +--- + +## This Week’s Achievements + +1. **Translation of RAG-Generated Contexts** + - Translated ~70 RAG-generated context descriptions using DeepL. + - Shared English and Japanese translations with mentors Walter and Devin for review. + - For Japanese, provided both **Kana** and **Kanji** variants to ensure localization accuracy. + +2. **Batch Processing Pipeline Development** + - Initiated work on a batch-processing system to automate RAG context generation for all 1535 msgid entries in the translation .po file. + - This will drastically reduce manual overhead and improve coverage. + +3. **Planning for Context Maintenance Workflow** + - Designed a future-proofing plan to automatically detect newly added or reused msgids in pull requests. + - Began outlining a GitHub Actions-based workflow to regenerate context chunks when changes are merged into the repo. + +--- + +## Challenges & How I Overcame Them + +- **Challenge:** Japanese localization required thoughtful distinction between script types (Kana vs Kanji). + **Solution:** Generated both forms using translation tools and consulted native guidance to ensure cultural appropriateness. + +- **Challenge:** Scaling RAG context generation to 1500+ entries without losing efficiency. + **Solution:** Started designing a batch system to streamline the entire generation process and set up hooks for automation in future updates. + +--- + +## Key Learnings + +- Multi-language support requires nuanced translation strategies, especially for languages like Japanese. +- Batch automation is essential when working with large-scale i18n datasets and AI-generated content. +- Proactive planning for long-term maintenance helps keep i18n tooling relevant as the codebase evolves. + +--- + +## Next Week’s Roadmap + +- Complete batch-processing implementation for generating RAG context for all msgids. +- Add persistence/storage layer to cache generated results and avoid recomputation. +- Set up a GitHub workflow for regenerating context on new PRs that modify or add translation strings. + +--- + +## Resources & References + +- **Music Blocks Repository:** [github.com/sugarlabs/musicblocks](https://github.com/sugarlabs/musicblocks) +- **DeepL Translator API:** [deepl.com/docs-api](https://www.deepl.com/docs-api) +- **GitHub Actions Docs:** [docs.github.com/actions](https://docs.github.com/actions) +- **RAG Concepts:** [arxiv.org/abs/2005.11401](https://arxiv.org/abs/2005.11401) + +--- + +## Acknowledgments + +Thanks to mentors Walter Bender and Devin Ulibarri for their ongoing guidance, especially on translation validation and workflow design. + +--- From 00068a7e1506e086d564ff084a31e7b03466e6d3 Mon Sep 17 00:00:00 2001 From: ac-mmi Date: Sun, 6 Jul 2025 15:40:24 +0530 Subject: [PATCH 4/4] DMP 25 week 04 blog by Aman Chadha --- .../posts/dmp-25-AmanChadha-week04.md | 83 +++++++++++++++++++ 1 file changed, 83 insertions(+) create mode 100644 src/constants/MarkdownFiles/posts/dmp-25-AmanChadha-week04.md diff --git a/src/constants/MarkdownFiles/posts/dmp-25-AmanChadha-week04.md b/src/constants/MarkdownFiles/posts/dmp-25-AmanChadha-week04.md new file mode 100644 index 00000000..2ae1d29b --- /dev/null +++ b/src/constants/MarkdownFiles/posts/dmp-25-AmanChadha-week04.md @@ -0,0 +1,83 @@ +--- +title: "DMP '25 Week 04 Update by Aman Chadha" +excerpt: "Completed context generation for all UI strings and submitted Turkish translations using DeepL with RAG-generated context" +category: "DEVELOPER NEWS" +date: "2025-06-30" +slug: "2025-06-30-dmp-25-aman-chadha-week04" +author: "@/constants/MarkdownFiles/authors/aman-chadha.md" +tags: "dmp25,sugarlabs,week04,aman-chadha" +image: "assets/Images/c4gt_DMP.png" +--- + + + +# Week 04 Progress Report by Aman Chadha + +**Project:** [JS Internationalization with AI Translation Support](https://github.com/sugarlabs/musicblocks/pull/4459) +**Mentors:** [Walter Bender](https://github.com/walterbender), [Devin Ulibarri](https://github.com/devinulibarri) +**Reporting Period:** 2025-06-24 – 2025-06-30 + +--- + +## Goals for This Week + +- Complete RAG-based context generation for **all UI strings** in the `.po` file. +- Translate the Turkish `.po` file using DeepL with generated context. +- Share Turkish translation with mentors for review and validation of context effectiveness. + +--- + +## This Week’s Achievements + +1. **Full Context Generation Completed** + - Successfully generated context for all 1,536 active `msgid` entries using the RAG (Retrieval-Augmented Generation) model. + - Ensured each UI string now has an associated contextual description to guide translators. + +2. **Turkish Translation via DeepL with Context** + - Used the DeepL API to translate the Turkish `.po` file, injecting the RAG-generated context for each `msgid`. + - This serves as a real-world test to evaluate how well contextual guidance improves translation accuracy and usability. + - Currently awaiting feedback on the quality of Turkish translations to assess the effectiveness of the context-driven approach. + +--- + +## Challenges & How I Addressed Them + +- **Challenge:** Integrating RAG-generated context into `.po` translation pipeline. + **Solution:** Adapted the `.po` processing script to pair each `msgid` with its context before sending it to DeepL, ensuring translators benefit from semantic clarity. + +- **Challenge:** Validating quality of translations in a language I do not speak. + **Solution:** Coordinated with mentors to review Turkish output and identify whether contextual enrichment improved translation fidelity. + +--- + +## Key Learnings + +- Contextual guidance significantly strengthens AI-driven translation quality, especially for UI-specific phrases. +- Systematic pairing of context with each string allows scalable improvements across languages. +- Human review remains crucial to validate AI-generated translations and refine context generation methods. + +--- + +## Next Week’s Roadmap + +- Collect and analyze mentor feedback on the Turkish `.po` file. +- Fine-tune the RAG context generation logic based on observed shortcomings, if any. +- Generalize the context-injection workflow for use with other languages (e.g., Spanish, French). +- Begin documenting the context generation + translation pipeline for future contributors. + +--- + +## Resources & References + +- **Music Blocks Repository:** [github.com/sugarlabs/musicblocks](https://github.com/sugarlabs/musicblocks) +- **DeepL Translator API:** [deepl.com/docs-api](https://www.deepl.com/docs-api) +- **GitHub Actions Docs:** [docs.github.com/actions](https://docs.github.com/actions) +- **RAG Concepts:** [arxiv.org/abs/2005.11401](https://arxiv.org/abs/2005.11401) + +--- + +## Acknowledgments + +Thanks to mentors Walter Bender and Devin Ulibarri for their feedback, review assistance, and continued support in improving translation workflows. + +---