
Audrey Clevy contributed to the etalab-ia/OpenGateLLM repository by developing features that enhance both sustainability tracking and developer onboarding. She implemented a carbon footprint calculation system for AI model inferences, integrating new parameters into model configurations and refactoring core components for improved accuracy and robustness. Using Python and YAML, she ensured that carbon data is computed, stored, and logged alongside usage statistics, supporting transparency in environmental impact reporting. Audrey also reorganized and expanded documentation, including detailed usage guides for AI code assistants across multiple IDEs, which streamlined onboarding and clarified configuration management for new contributors and users of the project.

October 2025 monthly summary for etalab-ia/OpenGateLLM focusing on improving developer onboarding and usage clarity through enhanced AI Code Assistant documentation. No critical bugs fixed this month. Key features delivered centered on documentation enhancements, including cross-IDE usage guides and a version bump, plus explicit kilo extension mention in docs.
October 2025 monthly summary for etalab-ia/OpenGateLLM focusing on improving developer onboarding and usage clarity through enhanced AI Code Assistant documentation. No critical bugs fixed this month. Key features delivered centered on documentation enhancements, including cross-IDE usage guides and a version bump, plus explicit kilo extension mention in docs.
June 2025 monthly summary for etalab-ia/OpenGateLLM: Delivered carbon footprint calculation and environmental impact tracking for AI model usage. Implemented end-to-end feature to compute and store carbon data, integrated new parameters into model configurations, and refactored core components to improve accuracy and robustness. Added tests and documentation to ensure reliability and onboarding clarity. This work enhances governance, transparency, and sustainability reporting for model usage across supported types.
June 2025 monthly summary for etalab-ia/OpenGateLLM: Delivered carbon footprint calculation and environmental impact tracking for AI model usage. Implemented end-to-end feature to compute and store carbon data, integrated new parameters into model configurations, and refactored core components to improve accuracy and robustness. Added tests and documentation to ensure reliability and onboarding clarity. This work enhances governance, transparency, and sustainability reporting for model usage across supported types.
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