RuntimeErrorSage: Intelligent Runtime Error Analysis and Remediation using Local Large Language Models

RuntimeErrorSage is a .NET middleware system designed to intelligently analyze and remediate runtime errors using a locally hosted Large Language Model (LLM), specifically Qwen 2.5 7B Instruct 1M. Unlike cloud-based tools, RuntimeErrorSage operates entirely offline, ensuring data privacy and low-latency error resolution. It intercepts unhandled exceptions, generates structured context via the Model Context Protocol (MCP), and utilizes an LLM to suggest and execute safe remediation actions. This research presents a formal system model for runtime error classification, context graph analysis, and remediation decision-making. Our theoretical analysis targets 80% accuracy in error root cause identification and 70% success rate in remediation suggestions. The system is designed for integration into ASP.NET Core applications, providing a promising approach to runtime error handling without external dependencies. Validation and further development are ongoing.