etalab-ia/OpenGateLLM
Jun 2025 – Jun 2025
1 Month active
Languages Used
MarkdownPythonYAML
Technical Skills
API IntegrationAlembicBackend DevelopmentCI/CDDatabase ConfigurationDatabase Management
Audrey_CLEVY
PROFILE
Audrey_clevy
Audrey Clevy contributed to the etalab-ia/OpenGateLLM repository by developing two core features focused on developer experience and sustainability. She authored comprehensive AI IDE integration guides, enabling seamless setup of AI code models in popular environments like VS Code and PyCharm, and supported local AI assistants through Continue and ProxyAI plugins. Using Python, SQLAlchemy, and Alembic, Audrey also implemented environmental footprint tracking in usage logging, persisting min/max kWh and kgCO2eq metrics in the database and validating them with integration tests. Her work improved onboarding, observability, and data integrity, laying a foundation for scalable, energy-aware backend development.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
5Total
Bugs
0
Commits
5
Features
2
Lines of code
191
Activity Months1
Your Network
20 people
Work History
June 2025
5 Commits • 2 Features
Jun 1, 2025June 2025 performance summary for etalab-ia/OpenGateLLM: Overview: - Delivered developer-focused features with an emphasis on IDE integration, observability, and sustainability metrics. Strengthened data integrity through migrations and test coverage, enabling scalable future work. Key features delivered: - AI IDE Integration Guides: Documentation and setup guides for integrating AI code models into popular IDEs (VS Code, IntelliJ/PyCharm) and enabling local AI assistants via Continue/ProxyAI plugins. Commits: c30dff20b748f6c0618ab637fb94fe866618c210; 5b385d1c603f9a471157f9893b8fcc1c52c08273. - Environmental footprint tracking in usage logging: Track environmental impact metrics (min/max kWh and kgCO2eq) in usage logging, persist in the database, and validate via integration tests. Commits: ef03cb30ce4f85e918bddbd2d07bfb7d897250b1; dc51bf0f7e6cc325bc18b56c584d729307b7a28c; dc30679510b83689c98e91191441071a5fd79c6b. Major bugs fixed: - No explicit bug fixes reported for June 2025. Notable robustness improvements include added integration tests for environmental footprint tracking and a database migration to support new metrics, reducing regression risk. Overall impact and accomplishments: - Accelerated developer onboarding and adoption of AI capabilities by providing concrete IDE integration documentation, enabling faster time-to-value for IDE-based AI workflows. - Improved observability and sustainability reporting by embedding footprint metrics into usage data and ensuring data persistence and test validation, supporting product KPIs around energy usage and emissions. - Strengthened platform resilience with a concrete Alembic migration for API DB and expanded integration test coverage for environmental footprint features. Technologies/skills demonstrated: - Documentation and developer experience design for IDE integrations - Python-based feature development, including plugin-era integrations - Database migrations (Alembic) and schema evolution - Usage logging instrumentation and metrics collection (min/max kWh, kgCO2eq) - End-to-end testing and integration testing to validate new capabilities
5 Commits • 2 Features
Jun 1, 2025June 2025 performance summary for etalab-ia/OpenGateLLM: Overview: - Delivered developer-focused features with an emphasis on IDE integration, observability, and sustainability metrics. Strengthened data integrity through migrations and test coverage, enabling scalable future work. Key features delivered: - AI IDE Integration Guides: Documentation and setup guides for integrating AI code models into popular IDEs (VS Code, IntelliJ/PyCharm) and enabling local AI assistants via Continue/ProxyAI plugins. Commits: c30dff20b748f6c0618ab637fb94fe866618c210; 5b385d1c603f9a471157f9893b8fcc1c52c08273. - Environmental footprint tracking in usage logging: Track environmental impact metrics (min/max kWh and kgCO2eq) in usage logging, persist in the database, and validate via integration tests. Commits: ef03cb30ce4f85e918bddbd2d07bfb7d897250b1; dc51bf0f7e6cc325bc18b56c584d729307b7a28c; dc30679510b83689c98e91191441071a5fd79c6b. Major bugs fixed: - No explicit bug fixes reported for June 2025. Notable robustness improvements include added integration tests for environmental footprint tracking and a database migration to support new metrics, reducing regression risk. Overall impact and accomplishments: - Accelerated developer onboarding and adoption of AI capabilities by providing concrete IDE integration documentation, enabling faster time-to-value for IDE-based AI workflows. - Improved observability and sustainability reporting by embedding footprint metrics into usage data and ensuring data persistence and test validation, supporting product KPIs around energy usage and emissions. - Strengthened platform resilience with a concrete Alembic migration for API DB and expanded integration test coverage for environmental footprint features. Technologies/skills demonstrated: - Documentation and developer experience design for IDE integrations - Python-based feature development, including plugin-era integrations - Database migrations (Alembic) and schema evolution - Usage logging instrumentation and metrics collection (min/max kWh, kgCO2eq) - End-to-end testing and integration testing to validate new capabilities
June 2025
Activity
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Quality Metrics
Correctness94.0%
Maintainability92.0%
Architecture92.0%
Performance88.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
MarkdownPythonYAML
Technical Skills
API IntegrationAlembicBackend DevelopmentCI/CDDatabase ConfigurationDatabase ManagementDatabase MigrationDocumentationIDE IntegrationIntegration TestingSQLAlchemy
Repositories Contributed To
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