DrAlzahraniProjects/csusb_fall2024_cse6550_team1
Nov 2024 – Nov 2024
1 Month active
Languages Used
Python
Technical Skills
Data CleaningNatural Language ProcessingWeb Scraping
bhavya
PROFILE
Bhavya
Worked on the DrAlzahraniProjects/csusb_fall2024_cse6550_team1 repository to enhance data preprocessing for retrieval-augmented generation systems. Developed an HTML cleaning feature in Python, leveraging BeautifulSoup for web scraping and data cleaning tasks. The solution systematically removed scripts, styles, headers, footers, and navigation elements from raw HTML, ensuring that only relevant text was extracted for downstream processing. By integrating this sanitizer into the RAG.py preprocessing pipeline, the work improved the quality of data used for embedding and retrieval, reducing noise and enhancing the reliability of search results. The contribution focused on robust, maintainable code for natural language processing workflows.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
35
Activity Months1
Your Network
43 peopleWork History
November 2024
1 Commits • 1 Features
Nov 1, 2024November 2024 monthly summary: Delivered HTML cleaning for RAG data preprocessing to improve data quality for the retrieval-augmented generation system. Implemented a BeautifulSoup-based sanitizer in RAG.py to strip scripts, styles, headers, footers, and navigation elements from raw HTML before text extraction, resulting in cleaner, more relevant text for indexing and retrieval. This reduces noise in the data pipeline, enhancing retrieval accuracy and downstream generation reliability.
1 Commits • 1 Features
Nov 1, 2024November 2024 monthly summary: Delivered HTML cleaning for RAG data preprocessing to improve data quality for the retrieval-augmented generation system. Implemented a BeautifulSoup-based sanitizer in RAG.py to strip scripts, styles, headers, footers, and navigation elements from raw HTML before text extraction, resulting in cleaner, more relevant text for indexing and retrieval. This reduces noise in the data pipeline, enhancing retrieval accuracy and downstream generation reliability.
November 2024
Activity
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture80.0%
Performance60.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
Data CleaningNatural Language ProcessingWeb Scraping
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