Haystack

Haystack is an open source AI orchestration framework developed by deepset for building production-ready retrieval-augmented generation (RAG) pipelines and agentic AI applications. It provides a modular, composable architecture that enables developers to create transparent, customizable AI systems with full visibility into every decision the AI makes. The framework supports moving from prototype to production using unified tooling for building, testing, and shipping AI use cases.

• Modular Pipeline Architecture allows orchestrating every step of AI agents from retrieval to reasoning to tool use, with support for branching and looping to handle complex agent workflows.

• Vendor-Agnostic Integrations connect to OpenAI, Anthropic, Mistral, Hugging Face, Weaviate, Pinecone, Elasticsearch, and many more providers without vendor lock-in, letting you mix and match components.

• Advanced RAG Capabilities enable building highly performant RAG pipelines with multiple retrieval and generation strategies including hybrid retrieval and self-correction loops.

• Agentic Pipelines feature a standard function-calling interface across all LLM generators so models can leverage tools to achieve more complex tasks.

• Multimodal AI Support handles not just text but also image processing, image generation, and audio transcription for next-generation AI applications.

• Conversational AI provides standardized chat interfaces across all generators for building chatbots and conversational agents.

• Content Generation offers flexible and composable prompt flows with Jinja-2 templates to build content generation engines matching specific workflows.

• Enterprise-Ready Deployment with serializable, cloud-agnostic, and Kubernetes-ready pipelines including built-in logging, monitoring, and observability support.

To get started, install Haystack using pip with pip install haystack-ai. The framework includes extensive documentation, tutorials, walkthroughs, and a cookbook with practical examples. Developers can access community support through Discord and GitHub Discussions, or upgrade to enterprise support for production deployments requiring private engineering assistance and deployment guides.