Results for “rgb”

Builds a Streamlit and FastAPI RAG application that lets users upload documents and query them with natural language through LM Studio.

Evaluates RAG pipelines using a filesystem-based benchmark with corpus/ and train.json, running evaluate_rag.py to tune retrieval and generation flags and interpret RAGAS metrics.

Expert guidance for architecting, developing, and operating SurrealDB 3, covering SurrealQL, multi-model data modeling, vector search, security, deployment, performance tuning, SDK integration, and ecosystem tools.

Designs and implements RAG pipelines, covering document chunking, embedding strategies, hybrid search, answer synthesis with source attribution, and evaluation using RAGAS metrics.