Generate RAG Test Sets in Python with Ragas: Build Evals from Your Docs
About this lesson
Most RAG evaluations fail before they start — generate a synthetic RAG test set from your docs to make retrieval regressions measurable. Get reproducible questions and reference answers so you can quantify context_precision, detect retrieval/answer drops, and make retriever changes actionable. Hands-on demo uses Ragas, OpenAI LLMs, embeddings, Hugging Face Dataset and a simple Python retriever — scalable to ANN indexes. Subscribe for practical AI engineering and LLM systems tutorials from Professor Py. #RAG #RetrievalAugmentedGeneration #LLM #AIEngineering #Python #Ragas #HuggingFace
Original Description
Most RAG evaluations fail before they start — generate a synthetic RAG test set from your docs to make retrieval regressions measurable.
Get reproducible questions and reference answers so you can quantify context_precision, detect retrieval/answer drops, and make retriever changes actionable.
Hands-on demo uses Ragas, OpenAI LLMs, embeddings, Hugging Face Dataset and a simple Python retriever — scalable to ANN indexes.
Subscribe for practical AI engineering and LLM systems tutorials from Professor Py.
#RAG #RetrievalAugmentedGeneration #LLM #AIEngineering #Python #Ragas #HuggingFace
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