The outcome

Create a reproducible retrieval workflow that answers from approved sources instead of model memory alone.

LlamaIndex is a open-source data framework for retrieval-augmented generation and agent workflows. Loading and indexing private data, building source-grounded retrieval applications, composing workflows and agents, and evaluating retrieval and response quality. This guide narrows that broad capability into one repeatable outcome, with checkpoints that keep the source material and your judgment in the loop.

Before you begin

Set the boundary before the tool starts.

Choose one real task, identify who will use the result, and decide what evidence or test will make the result acceptable. Gather only the source material needed for that task. If the work contains confidential, personal, regulated, or client-owned information, confirm that the platform and account are approved before sharing it.

Troiana principle

AI should make the work easier to inspect. If the workflow removes the source, the owner, or the review step, redesign the workflow.

Step by step

A workflow you can repeat.

  1. 01

    Define the corpus owner, allowed questions, freshness rules, access policy, citation requirements, and a benchmark with expected sources.

  2. 02

    Load clean documents with stable IDs and metadata, remove duplicates and secrets, then choose chunking and embedding settings deliberately.

  3. 03

    Build and persist the index, configure retrieval depth and filters, and ensure tenant or document permissions apply before generation.

  4. 04

    Run the benchmark and inspect retrieved nodes separately from final answers for relevance, missed evidence, conflicts, and leakage.

  5. 05

    Tune one retrieval variable at a time, version the corpus and index configuration, and schedule refresh and regression evaluation.

Working standard

What good use looks like.

  • Evaluate retrieval before generation.
  • Preserve source IDs and metadata.
  • Enforce permissions during retrieval.

RAG can retrieve irrelevant, stale, private, or malicious content and still produce fluent answers. Enforce access during retrieval, sanitize sources, preserve citations, separate retrieval and response evaluation, and protect traces and model credentials.

Official references

Check the current product documentation.

Features, plan limits, availability, and data controls change. These official pages are the starting points used for this collection.