AI4Bharat/Anudesh-Backend
Nov 2024 – Dec 2024
2 Months active
Languages Used
DjangoPythonSQLYAML
Technical Skills
API DevelopmentAnnotation SystemsBackend DevelopmentData AnalysisData ProcessingData Validation
Kunal Tiwary
PROFILE
Kunal Tiwary
Kunal Tiwary contributed to the AI4Bharat/Anudesh-Backend repository by developing and refining backend features that enhanced data quality, annotation workflows, and evaluation metrics. He implemented multi-annotator assignment flows, enriched annotator data with access controls, and introduced Word Error Rate (WER) metrics for annotation reviews and LLM prompt comparisons. Using Django, Python, and SQL, Kunal improved backend reliability through robust error handling and validation, streamlined task filtering, and upgraded CI/CD workflows with automated linting and formatting. His work addressed data integrity and scalability, enabling more reliable annotation operations and measurable quality insights across diverse language and evaluation project types.
Overall Statistics
Feature vs Bugs
82%Features
Repository Contributions
34Total
Bugs
2
Commits
34
Features
9
Lines of code
2,073
Activity Months2
Your Network
9 peopleWork History
December 2024
19 Commits • 4 Features
Dec 1, 2024December 2024 backend-focused month for AI4Bharat/Anudesh-Backend: Implemented core evaluation metrics, improved data quality, and hardened reliability, delivering measurable business value for model evaluation, user experience, and deployment velocity. Key features delivered across the repository include WER calculation/reporting for InstructionDrivenChat and LLM prompts with cross-prompt comparison and average reporting; enrichment and validation of data for MultipleInteractionEvaluation projects; backend reliability and error handling enhancements; CI/CD tooling and formatting improvements; and a targeted bug fix in value comparison logic.
19 Commits • 4 Features
Dec 1, 2024December 2024 backend-focused month for AI4Bharat/Anudesh-Backend: Implemented core evaluation metrics, improved data quality, and hardened reliability, delivering measurable business value for model evaluation, user experience, and deployment velocity. Key features delivered across the repository include WER calculation/reporting for InstructionDrivenChat and LLM prompts with cross-prompt comparison and average reporting; enrichment and validation of data for MultipleInteractionEvaluation projects; backend reliability and error handling enhancements; CI/CD tooling and formatting improvements; and a targeted bug fix in value comparison logic.
December 2024
November 2024
15 Commits • 5 Features
Nov 1, 2024For 2024-11, AI4Bharat/Anudesh-Backend delivered core enhancements to improve data quality, collaboration, and reliability across the annotation lifecycle. Highlights include annotator data enrichment with notes propagation and access controls; scalable multi-annotator assignment flow; stable annotation ordering for reviewer chronology; WER-based quality metrics across annotation stages; and language support (Thai/Burmese) with enhanced filtering and robust task filtering to prevent crashes in review workflows. These changes increase data integrity, enable scalable annotation operations, and provide measurable quality insights for project types.
November 2024
15 Commits • 5 Features
Nov 1, 2024For 2024-11, AI4Bharat/Anudesh-Backend delivered core enhancements to improve data quality, collaboration, and reliability across the annotation lifecycle. Highlights include annotator data enrichment with notes propagation and access controls; scalable multi-annotator assignment flow; stable annotation ordering for reviewer chronology; WER-based quality metrics across annotation stages; and language support (Thai/Burmese) with enhanced filtering and robust task filtering to prevent crashes in review workflows. These changes increase data integrity, enable scalable annotation operations, and provide measurable quality insights for project types.
Activity
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Quality Metrics
Correctness83.6%
Maintainability86.4%
Architecture79.2%
Performance73.8%
AI Usage23.6%
Skills & Technologies
Programming Languages
DjangoPythonSQLYAML
Technical Skills
API DevelopmentAnnotation SystemsBackend DevelopmentCI/CDCode FormattingData AnalysisData ProcessingData ValidationDatabase ManagementDevOpsDjangoError HandlingGitHub ActionsMachine LearningPython
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