BU-Spark/ml-bpl-rag
Nov 2025 – Dec 2025
2 Months active
Languages Used
PythonJSON
Technical Skills
Pythondata analysisdata processingmachine learningAIPython programming
pnylin0720
PROFILE
Pnylin0720
Penny Lin developed a Language Model Evaluation Framework for the BU-Spark/ml-bpl-rag repository, focusing on automating the assessment of large language model outputs. Using Python and leveraging data analysis and machine learning techniques, Penny designed the framework to process CSV inputs, evaluate each entry across metrics such as answer relevancy, contextual recall, and precision, and output results in both CSV and JSON formats. In a subsequent enhancement, Penny improved context data parsing and reporting clarity, enabling more reliable and actionable evaluation summaries. The work demonstrated depth in data processing and validation, providing a scalable foundation for consistent model benchmarking and reporting.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
4Total
Bugs
0
Commits
4
Features
2
Lines of code
1,174
Activity Months2
Your Network
67 people
Work History
December 2025
3 Commits • 1 Features
Dec 1, 2025December 2025 (BU-Spark/ml-bpl-rag) monthly summary focused on delivering measurable business value through DeepEval evaluation enhancements and improved reporting. The dominant delivery was the DeepEval Evaluation Enhancements feature, which consolidates robust context data parsing, adds an evaluation metrics JSON, and produces clearer evaluation results summaries for faster, data-driven decisions in the RAG pipeline.
3 Commits • 1 Features
Dec 1, 2025December 2025 (BU-Spark/ml-bpl-rag) monthly summary focused on delivering measurable business value through DeepEval evaluation enhancements and improved reporting. The dominant delivery was the DeepEval Evaluation Enhancements feature, which consolidates robust context data parsing, adds an evaluation metrics JSON, and produces clearer evaluation results summaries for faster, data-driven decisions in the RAG pipeline.
December 2025
November 2025
1 Commits • 1 Features
Nov 1, 2025Delivered a Language Model Evaluation Framework in BU-Spark/ml-bpl-rag to automate evaluation of LLM outputs across metrics including answer relevancy, contextual recall, and contextual precision. The framework ingests CSV input, processes each entry, and outputs results in both CSV and JSON formats, enabling streamlined reporting and benchmarking. This work reduces manual evaluation effort and provides a scalable foundation for consistent model comparisons across experiments.
November 2025
1 Commits • 1 Features
Nov 1, 2025Delivered a Language Model Evaluation Framework in BU-Spark/ml-bpl-rag to automate evaluation of LLM outputs across metrics including answer relevancy, contextual recall, and contextual precision. The framework ingests CSV input, processes each entry, and outputs results in both CSV and JSON formats, enabling streamlined reporting and benchmarking. This work reduces manual evaluation effort and provides a scalable foundation for consistent model comparisons across experiments.
Activity
Loading activity data...
Quality Metrics
Correctness90.0%
Maintainability85.0%
Architecture85.0%
Performance85.0%
AI Usage50.0%
Skills & Technologies
Programming Languages
JSONPython
Technical Skills
AIPythonPython programmingdata analysisdata evaluationdata parsingdata processingdata validationmachine learning
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline