teamg4it/g4it
May 2025 – Jun 2025
2 Months active
Languages Used
HTMLSCSSTypeScriptJavaXMLYAML
Technical Skills
API IntegrationAngularForm HandlingFront-end DevelopmentFrontend DevelopmentPrimeNG
mafofana
PROFILE
Mafofana
Mamba-Makagbe Fofana developed and integrated a unified AI service parameters configuration form within the teamg4it/g4it repository, consolidating model details, quantization, and inference options to streamline digital service onboarding and reduce configuration errors. Leveraging Angular, TypeScript, and PrimeNG on the frontend, Fofana implemented logic to estimate token generation and removed legacy components to simplify maintenance. On the backend, using Java, Spring Boot, and JPA, Fofana delivered a modular AI recommendations retrieval service, exposing a REST API and updating OpenAPI documentation. The work demonstrated careful configuration management, including a rollback for stability, and laid groundwork for future AI-driven features.
Overall Statistics
Feature vs Bugs
67%Features
Repository Contributions
6Total
Bugs
1
Commits
6
Features
2
Lines of code
4,959
Activity Months2
Your Network
28 peopleSame Organization
@etudiant.univ-rennes.fr5
Work History
June 2025
4 Commits • 1 Features
Jun 1, 2025June 2025 monthly summary for teamg4it/g4it focusing on end-to-end feature delivery, stability work, and technical competency demonstrated across the repository.
4 Commits • 1 Features
Jun 1, 2025June 2025 monthly summary for teamg4it/g4it focusing on end-to-end feature delivery, stability work, and technical competency demonstrated across the repository.
June 2025
May 2025
2 Commits • 1 Features
May 1, 2025May 2025 monthly summary: Delivered a unified AI service parameters configuration form, integrated into the digital services footprint module, including model details, framework, quantization, and inference/finetuning options with logic to estimate total token generation from user and request inputs. Completed legacy cleanup by deprecating/removing the legacy IA parameter components (AI infrastructure side panel and cloud services) to consolidate AI service parameter configuration under the new form. This consolidation reduces maintenance overhead, lowers configuration errors, and accelerates onboarding for AI service configurations, aligning with our AI infra strategy and improving end-to-end service reliability.
May 2025
2 Commits • 1 Features
May 1, 2025May 2025 monthly summary: Delivered a unified AI service parameters configuration form, integrated into the digital services footprint module, including model details, framework, quantization, and inference/finetuning options with logic to estimate total token generation from user and request inputs. Completed legacy cleanup by deprecating/removing the legacy IA parameter components (AI infrastructure side panel and cloud services) to consolidate AI service parameter configuration under the new form. This consolidation reduces maintenance overhead, lowers configuration errors, and accelerates onboarding for AI service configurations, aligning with our AI infra strategy and improving end-to-end service reliability.
Activity
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Quality Metrics
Correctness83.4%
Maintainability83.4%
Architecture83.4%
Performance73.4%
AI Usage20.0%
Skills & Technologies
Programming Languages
HTMLJavaSCSSTypeScriptXMLYAML
Technical Skills
API DesignAPI DevelopmentAPI IntegrationAngularBackend DevelopmentData MappingDatabase ManagementForm HandlingFront-end DevelopmentFrontend DevelopmentJPAOpenAPIPrimeNGREST APIREST APIs
Repositories Contributed To
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