AxionSys - Local-first AI debugging intelligence

AxionSys is a completely offline, local-first AI debugging assistant built for developers who need deep code analysis without compromising privacy or relying on cloud APIs. Built and optimized to run on consumer hardware (like AMD Radeon GPUs via ROCm and Ollama), AxionSys acts as an autonomous debugging expert that sits right on your machine. The Workflow The system takes two inputs: a repository (either a local directory or a pasted GitHub URL) and an error log, traceback, or simple error message. AxionSys parses the log to extract structured queries and immediately prioritizes any files mentioned in the traceback. It then searches your entire codebase using a highly accurate Hybrid Retrieval system, combining dense vector embeddings (FAISS) with sparse keyword matching (BM25) to find the most relevant code chunks. Intelligent Analysis Instead of just returning search results, AxionSys uses an advanced LLM reranker with dynamic fusion scoring to guarantee the most relevant files are pushed to the top. The context is then passed to a Root Cause Engine powered by a local Qwen 3.5 9B model. The engine performs causal chain reasoning to trace how a bug propagates across multiple files, mapping out the precise call chain from [OK] to [BUG] to [CRASH]. Actionable Outputs AxionSys doesn't just tell you what went wrong; it tells you how to fix it. The final output provides: A plain-English Root Cause Analysis explaining the exact failure point. A Call Chain Visualization showing how the error cascaded through your architecture. A concrete Unified Diff Patch that can be directly applied to your code. Confidence Scores for both the diagnosis and the generated fix. Complete with an intuitive React frontend and a robust FastAPI backend, AxionSys offers enterprise-grade AI debugging with zero cloud dependencies, zero latency from network calls, and absolute data privacy.