Results for “retrieval-evaluation”
7 skills
alirezarezvani RAG Architect
Design, tune, and evaluate production RAG pipelines with deterministic tools for chunking, pipeline design, and retrieval evaluation.
20.4k · bundle
nvidia Nemotron Retrieval Recipes
Plan, debug, tune, evaluate, export, or deploy public Nemotron embedding and reranking retrieval recipes using the current checkout.
2.2k · bundle
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majiayu000 RAG
Builds Retrieval-Augmented Generation systems with document chunking, embedding generation, vector storage, and retrieval pipelines, including evaluation and optimization.
567 · bundle
github Qdrant Search Strategies
Guides selection of Qdrant search strategies including hybrid search, reranking, relevance feedback, MMR, and discovery APIs to improve retrieval quality.
36.2k
jeffallan RAG Architect
Designs and implements production-grade RAG systems by chunking documents, generating embeddings, configuring vector stores, building hybrid search pipelines, applying reranking, and evaluating retrieval quality.
10.4k · bundle
affaan-m Iterative Retrieval
Progressively refines context retrieval in multi-agent workflows to solve the subagent context problem.
226k
nvidia RAG Eval
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.
2.2k · bundle