We've overhauled our RAG implementation to provide much richer, more accurate responses. This includes increasing content truncation limits, raising token caps for context compression, expanding retrieval scope (topK and sources), and refining our system prompts for better synthesis and citation. These adjustments ensure the model has access to deeper context and produces more reliable, search-optimized output.