schwichtgit/ai-resume

# Technical Summary Implements hybrid semantic search (BM25 + vector embeddings + cross-encoder re-ranking) to ground LLM responses in resume content, backed by a portable `.mv2` vector database. The architecture spans Rust gRPC for sub-5ms semantic lookup, Python FastAPI for LLM orchestration with Server-Sent Events streaming, and React 19 frontend—all coordinated through a go-task build system and containerized with rootless, read-only deployments. Also exposes the resume agent as an MCP server for programmatic access from Claude, Cursor, and other compatible clients.