Haystack

Haystack is an open-source Python framework for building applications on top of large language models (LLMs), from retrieval pipelines to tool-using agents. The framework is maintained by deepset, a Berlin-based company founded in 2018, and released under the Apache 2.0 license.

Haystack centers on components and pipelines. A component does one job, such as embedding text, retrieving documents, or prompting an LLM, and a pipeline wires components into an explicit graph that defines how data flows.

Document Stores connect the retrieval side to vector databases such as Weaviate, Pinecone, and Elasticsearch, which makes Haystack a common choice for retrieval-augmented generation (RAG), semantic search, and multimodal applications. A RAG pipeline wires those pieces into one graph:

A query runs through embedder, retriever, prompt builder, and generator to an answer, backed by a Document Store on a vector database.
One Job per Component, Wired Into an Explicit Graph

An Agent abstraction pairs a chat model with tools for autonomous, multi-step workflows. Haystack stays vendor-agnostic, with integrations for OpenAI, Anthropic, Google, Hugging Face, and Amazon Bedrock, along with locally hosted models. Python developers install it from PyPI as haystack-ai, which needs Python 3.10 or later.

Haystack competes with other Python LLM frameworks. LlamaIndex and LangChain cover similar retrieval and agent ground, while Pydantic AI concentrates on type-safe agent definitions. Haystack orchestrates components rather than serving models or storing data itself, so you supply your own provider credentials and point Document Stores at a backend such as Weaviate or Elasticsearch. An in-memory store ships with the framework for prototyping.

Version 3.0, released in July 2026, targeted production agents with hooks around the agent loop, built-in state such as step counts and token usage, first-class skills, and ready-made agents for tasks like deep research. deepset also builds paid products on top of the framework, including the Haystack Enterprise Platform, and offers deepset Studio, a free visual builder that exports pipelines to Python or YAML.

Official website: haystack.deepset.ai

Embeddings and Vector Databases With ChromaDB

Tutorial

Embeddings and Vector Databases With ChromaDB

Vector databases are a crucial component of many NLP applications. This tutorial will give you hands-on experience with ChromaDB, an open-source vector database that's quickly gaining traction. Along the way, you'll learn what's needed to understand vector databases with practical examples.

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For additional information on related topics, take a look at the following resources:

By Martin Breuss • Updated Aug. 31, 2026
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