# Haystack — AI Orchestration for Search & RAG

> Open-source AI orchestration framework by deepset. Build production RAG pipelines, semantic search, and agent workflows with modular components. 25K+ GitHub stars.

## Install

Save as a script file and run:

## Quick Use

```bash
pip install haystack-ai
```

```python
from haystack import Pipeline
from haystack.components.generators import OpenAIGenerator
from haystack.components.builders import PromptBuilder

prompt = PromptBuilder(template="Answer: {{query}}")
llm = OpenAIGenerator(model="gpt-4o")

pipe = Pipeline()
pipe.add_component("prompt", prompt)
pipe.add_component("llm", llm)
pipe.connect("prompt", "llm")

result = pipe.run({"prompt": {"query": "What is RAG?"}})
print(result["llm"]["replies"][0])
```

---

## Intro

Haystack is an open-source AI orchestration framework by deepset for building production-ready RAG pipelines, semantic search engines, and agent workflows. It uses a modular pipeline architecture where you compose components (retrievers, generators, rankers, converters) into directed graphs. Supports 30+ LLM providers and vector stores. 25,000+ GitHub stars.

**Best for**: Teams building production RAG, search, or question-answering systems
**Works with**: OpenAI, Anthropic, Google, Cohere, Ollama, 30+ providers

---

## Core Concepts

### Pipelines
Compose components into DAGs — each component does one thing well:
```python
pipe.add_component("converter", HTMLToDocument())
pipe.add_component("splitter", DocumentSplitter(split_length=200))
pipe.add_component("embedder", OpenAIDocumentEmbedder())
pipe.add_component("writer", DocumentWriter(document_store=store))
pipe.connect("converter", "splitter")
pipe.connect("splitter", "embedder")
pipe.connect("embedder", "writer")
```

### Component Library
50+ built-in components: document converters, splitters, embedders, retrievers, rankers, generators, and more.

### Document Stores
Pluggable storage: Elasticsearch, Qdrant, Pinecone, Weaviate, ChromaDB, pgvector, and in-memory.

### Evaluation
Built-in evaluation metrics for RAG quality: faithfulness, context relevance, answer relevance.

---

### FAQ

**Q: What is Haystack?**
A: An open-source AI orchestration framework by deepset for building production RAG, search, and agent pipelines with modular components. 25K+ GitHub stars.

**Q: How is Haystack different from LangChain?**
A: Haystack uses a strict pipeline/DAG model with typed components, making it more predictable for production. LangChain is more flexible but less structured.

---

## Source & Thanks

> Created by [deepset](https://github.com/deepset-ai). Licensed under Apache 2.0.
> [deepset-ai/haystack](https://github.com/deepset-ai/haystack) — 25,000+ GitHub stars

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Source: https://tokrepo.com/en/workflows/761bd107-7156-4c62-b268-62a3fb9818dc
Author: Script Depot