@pranavpaharia88834

Setting up AI and ML environments shouldn't be a bottleneck. Yet, developers frequently struggle navigating fragmented documentation, complex compatibility matrices, and architectural differences between AMD Instinct™ and Radeon™ RX GPUs. ROCm-Pilot eliminates this friction as an intelligent, context-aware setup assistant built exclusively for the AMD ecosystem. ROCm-Pilot is a Retrieval-Augmented Generation (RAG) agent that automatically and safely introspects local hardware. Using read-only diagnostic tools like rocm-smi and rocminfo, it detects your exact GPU architecture (e.g., gfx942), OS, and drivers. Rather than hallucinating, the agent grounds its answers in an auto-updating vector database scraped from official AMD GitHub repositories and developer blogs. By utilizing a hybrid search pipeline—combining GPU-accelerated ChromaDB semantic embeddings with BM25 sparse keyword matching—it ensures pinpoint accuracy for release-specific nuances. The platform outputs perfectly tailored, copy-pasteable bash commands and configuration scripts with verifiable citations. ROCm-Pilot also leverages Astral’s uv for blazing-fast dependency isolation. To ensure strict data privacy, ROCm-Pilot features a dual-tiered LLM architecture. It runs entirely locally by inferencing Google’s Gemma-4 (12B) natively on AMD hardware. For headless environments, it seamlessly falls back to cloud APIs via the Lemonade SDK and Fireworks AI. We also built a custom Evaluation Harness to continuously test RAG retrieval accuracy against a golden dataset of AMD developer queries. By automating complex configurations, ROCm-Pilot accelerates developer onboarding across the entire AMD AI ecosystem.

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