Haystack

What is Haystack?

Haystack is an open-source Python framework for composing production AI systems from modular components. It is designed for retrieval-augmented generation, tool-using agents, context engineering, document processing, multimodal search, and other pipelines that need explicit control over data flow.

Components perform focused work such as document conversion, preprocessing, embedding, retrieval, generation, routing, tool invocation, or evaluation. Developers connect components into serializable pipelines with branches and loops, replace implementations without rewriting the full application, and deploy across cloud or self-managed infrastructure.

How to Use Haystack

1. Install the Haystack package in a Python project and define the target task and evaluation set.
2. Select document stores, converters, embedders, retrievers, generators, and tools from supported integrations.
3. Connect components into a pipeline and define branches, loops, and failure handling.
4. For agents, configure a tool-capable chat generator, Tool objects, and a ToolInvoker or Agent component.
5. Test retrieval quality, tool arguments, outputs, latency, cost, and failure cases.
6. Serialize and deploy the pipeline, then add logging, monitoring, evaluation, scaling, and access controls.

Core Features

• Modular components: Provides interchangeable building blocks with explicit inputs and outputs.
• Pipeline orchestration: Connects components into directed workflows with branching and looping.
• RAG support: Covers ingestion, document stores, embedding, retrieval, reranking, and generation.
• Agent tooling: Standardizes tool definitions, tool calling, invocation, and multi-step agent logic.
• Context engineering: Gives developers control over retrieved, transformed, and generated context.
• Broad integrations: Connects models, vector databases, document stores, evaluators, and external services.
• Serialization and deployment: Supports portable pipelines, cloud-agnostic operation, and Kubernetes deployments.
• Observability and evaluation: Provides patterns and integrations for logging, monitoring, datasets, and evaluators.

Use Cases

• Build enterprise search and question-answering over private documents.
• Create RAG assistants with hybrid retrieval and self-correction loops.
• Build agents that call APIs, pipelines, functions, and external tools.
• Process, index, and search text, images, and other document content.
• Develop controlled AI backends for support, research, analysis, and knowledge applications.

Pricing

Haystack is open source and can be used without a framework subscription. Users pay separately for chosen model APIs, vector databases, storage, compute, observability, and deployment infrastructure. deepset also offers enterprise support, with commercial terms handled separately.

Frequently Asked Questions

Is Haystack a hosted no-code agent builder?

No. It is primarily a Python framework for developers who want modular control over AI pipelines and agents.

Can components run outside a pipeline?

Some components can be used independently, while others are normally connected through a Pipeline.

Does open source make an application production-ready by itself?

No. Production teams still need security, secrets management, authorization, evaluation, monitoring, data governance, scaling, and incident handling.