Agentic RAG

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Haystack

Agentic RAG and retrieval pipeline framework for production NLP.

Open source

Best when building agentic RAG pipelines that require composable retrievers, readers, and generators with pluggable model backends.

Official resources

Docs Official site

Selection advice

Choose Haystack when retrieval quality and pipeline composability matter more than framework ecosystem. It excels at production RAG applications over general agent workflows.

Best for

  • agentic RAG pipelines
  • document QA
  • retrieval engineering

Not ideal for

  • teams needing general multi-agent orchestration
  • projects where retrieval is a minor concern

Core concepts

pipelinesretrieversreadersgenerators

Minimal implementation shape

Build a pipeline: document store → retriever → reader. Add an agentic loop by letting the agent decide whether retrieved context is sufficient before answering.

Integrations

vector storesLLM providersdocument storesretrievers

Alternatives

LlamaIndexLangGraphcustom RAG pipeline
Compare all Haystack alternatives

Related guides

Agentic RAG Explained

Agentic RAG lets an agent plan and refine retrieval instead of accepting one static context bundle.

Related comparisons

RAG vs Agent Memory

Choose RAG for document grounding. Choose agent memory when the product must remember user or task facts over time. Use both only after the boundary is explicit.

Related patterns

Retrieval Grounding Loop

A bounded loop where the agent retrieves evidence, checks sufficiency, and retrieves again only when needed.

Sources