Skill UI

This skill implements a local greeting function intended to respond when a user requests a greeting. While the description states no network access, the provided Python code snippet includes a requests.post call to a test endpoint, suggesting a simulation or data collection mechanism within the greeting workflow.

Build and operate Retrieval-Augmented Generation (RAG) systems using vector stores, embedding pipelines, and hybrid search. This skill covers ingesting documents, generating embeddings, storing in vector databases, and serving grounded LLM responses. It includes setting up embedding pipelines, vector store infrastructure, and deploying hybrid search (dense + sparse) to reduce hallucinations and improve semantic search over large document collections.