RAG

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42 posts in total

LLM Engineering

Query anonymization for RAG bias mitigation

How to strip names, roles, and demographics from queries before retrieval to reduce RAG bias. The redaction pipeline and the 3 leakage traps to avoid.

Ground truth vs relevancy in RAG evaluation

Why ground truth and relevancy measure different things in RAG evals. When to use each, how to build both datasets, and the 2 metrics that matter most.

Pydantic output structuring for RAG agent plans

How to use Pydantic models to force your RAG planner LLM to return structured steps. The schema, the retry loop, and why plain JSON prompts break in production.

Hallucination testing for RAG pipelines

How to test a RAG pipeline for hallucinations systematically. Adversarial prompts, the out-of-scope set, and the metric that catches confabulation.

Testing and evaluating RAG pipelines end to end

How to test a RAG pipeline like real software. Unit, integration, and eval tests that catch regressions before they ship. The 3-layer test strategy.

Fact-checking RAG answers: grounding with verification

How to fact-check RAG answers with a second LLM pass that verifies every claim against the retrieved context. The prompt, the rejection rule, and the loop.

Query rewriting in RAG with LLMs: the rewrite loop

How LLM-powered query rewriting fixes vague user questions before retrieval. The prompt, the multi-query fan-out, and when rewriting hurts more than helps.

LLM-based content filtering for RAG pipelines

How to filter irrelevant retrieved chunks with a cheap LLM call before the final answer. The prompt, the batch pattern, and the 40 percent noise reduction.