PCB-RAG: Conditional Retrieval over Multimodal PCB Component Datasheets

Electronic component datasheets are essential for PCB design, yet their multi modal content and conditional specifications challenge retrieval-augmented gen eration (RAG).Existing systems may retrieve semantically relevant but condition ally incompatible evidence, producing incorrect specifications . We propose PCB RAG, which formulates datasheet QA as condition-aware evidence acquisition . It constructs a conditional multimodal knowledge graph that separates property concepts from specification statements and compiles effective contexts through scoped inheritance and per-variable overrides . A shared property encoder aligns equivalent properties while distinguishing evidence applicability across condi tions . Guided by a structured query representation (CQIR), an evidence-state pol icy selects retrieval actions and verifies condition coverage before answer gener ation . We also introduce PCB-CQA, a four-task benchmark with strict data splits for evaluating answer correctness and evidence sufficiency. Experiments show that PCB-RAG outperforms strong baselines in accuracy and evidence reliability.