freshcrate
Skin:/
Home > RAG & Memory > haystack-cookbook

haystack-cookbook

๐Ÿ‘ฉ๐Ÿปโ€๐Ÿณ A collection of example notebooks using Haystack

Why this rank:Strong adoptionRecent releaseHealthy release cadence

Description

๐Ÿ‘ฉ๐Ÿปโ€๐Ÿณ A collection of example notebooks using Haystack

README

๐Ÿ‘ฉ๐Ÿปโ€๐Ÿณ Haystack Cookbook

Green logo of a stylized white 'H' with the text 'Haystack, by deepset. The Production-Ready Open Source AI Framework'ย Abstract green and yellow diagrams in the background.

๐Ÿง‘โ€๐Ÿณ๐ŸณDiscover The Haystack Cookbook here

A collection of example notebooks using Haystack ๐Ÿ’š

These examples can serve as guidelines for using different model providers, vector databases, retrieval techniques, new experimental features, and more with Haystack. Most showcase a specific, small demo.

To learn more about how to use Haystack, please visit our Docs and official Tutorials.

For more examples, you may also find our Blog useful.

Contributing to the Haystack Cookbook

If you have an example that uses Haystack, you can add it to this repository by creating a PR.

You can also create a PR directly from Colab by creating a fork of this repository and selecting "Save a Copy to GitHub" on Colab. Once you add your example to your fork, you can create a PR on this repository.

  1. Add your notebook to /notebooks folder
  2. Give a descriptive name to your file that includes the names of (if applicable) the model providers, databases, the technologies you use in your example, and/or the task you are completing in the example.
  3. Make sure you add it to index.toml, including its title and topics. If the notebook is using an experimental feature, also add the discussion link with the experimental = true field.

Release History

VersionChangesUrgencyDate
main@2026-10-08Latest activity on main branchHigh10/8/2026
0.0.0No release found โ€” using repo HEADHigh4/21/2026
main@2026-04-21Latest activity on main branchHigh4/21/2026

Dependencies & License Audit

Loading dependencies...

Similar Packages

sdk-pythonA model-driven approach to building AI agents in just a few lines of code.harness-cli/v0.2.2
samplesAgent samples built using the Strands Agents SDK.main@2026-10-21
docsDocumentation for the Strands Agents SDK. A model-driven approach to building AI agents in just a few lines of code. v0.1.0
golemGolem Cloud is the agent-native platform for building AI agents and distributed applications that never lose state, never duplicate work, and never require you to build infrastructure.v1.6.1
adk-pythonAn open-source, code-first Python toolkit for building, evaluating, and deploying sophisticated AI agents with flexibility and control.v2.13.0

More from deepset-ai

haystackOpen-source AI orchestration framework for building context-engineered, production-ready LLM applications. Design modular pipelines and agent workflows with explicit control over retrieval, routing, m

More in RAG & Memory

generative-ai-for-beginners21 Lessons, Get Started Building with Generative AI
ultralyticsUltralytics YOLO ๐Ÿš€ for SOTA object detection, multi-object tracking, instance segmentation, pose estimation and image classification.
azure-search-documentsMicrosoft Azure Cognitive Search Client Library for Python