Haystack for RAG
Haystack is an open‑source framework for building production‑ready RAG pipelines. It emphasises modularity, scalability, and includes built‑in evaluation tools.
Haystack: production‑oriented, with pipelines for indexing and querying.
Basic RAG Pipeline with Haystack
from haystack import Pipeline
from haystack.components.writers import DocumentWriter
from haystack.components.converters import PyPDFToDocument
from haystack.components.preprocessors import DocumentSplitter
from haystack.components.embedders import SentenceTransformersDocumentEmbedder
from haystack.components.retrievers import InMemoryBM25Retriever
from haystack.components.generators import OpenAIGenerator
# Indexing pipeline
indexing = Pipeline()
indexing.add_component("converter", PyPDFToDocument())
indexing.add_component("splitter", DocumentSplitter(split_by="word", split_length=500))
indexing.add_component("embedder", SentenceTransformersDocumentEmbedder())
indexing.add_component("writer", DocumentWriter(document_store))
indexing.connect("converter", "splitter"); indexing.connect("splitter", "embedder"); indexing.connect("embedder", "writer")
# Querying pipeline
query = Pipeline()
query.add_component("retriever", InMemoryBM25Retriever(document_store))
query.add_component("generator", OpenAIGenerator())
query.connect("retriever", "generator")Key Features
- Production‑ready: scalable, async support.
- Built‑in evaluation: compute metrics like recall, MRR.
- Support for many vector stores (FAISS, Elasticsearch, Qdrant, Pinecone).
- Pre‑built pipelines for RAG, summarisation, translation.
When to Use Haystack
Best for large‑scale production systems, teams needing built‑in evaluation, and when you prefer explicit pipeline components over chain‑based frameworks.
Two Minute Drill
- Haystack uses explicit pipelines for indexing and querying.
- Production‑ready, scalable.
- Includes evaluation tools.
- Good for large‑scale RAG deployments.
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