Worked on enhancing error handling and user-facing messaging for the fal-ai/fal repository, focusing on backend and API development using Python and gRPC. Developed a system that exposes error types and detailed information in HTTP responses, enabling more actionable diagnostics for users and operators. Introduced a classification mechanism for gRPC UNAVAILABLE errors, providing human-readable guidance and improving troubleshooting efficiency. Updated the command-line interface to display formatted error messages for various failure scenarios. Added comprehensive unit tests to validate the new error handling logic, ensuring robustness and compatibility across Python versions. These improvements streamline debugging and reduce mean time to resolution.