Haystack llms.txt
Browse Haystack documentation as markdown. Click any page in the sidebar to view it, or copy the full llms.txt for your AI tools.
What is Haystack's llms.txt?
Haystack publishes an /llms.txt file that provides AI systems with a structured index of its documentation. It follows the llms.txt specification, organizing links to guides, API references, and tutorials under section headings so that LLMs like ChatGPT, Claude, and Gemini can quickly understand what Haystack offers and where to find details.
Sections: Docs · Examples · Optional
Add Haystack Docs to Your AI Assistant
Select your tool to see how to add Haystack's llms.txt as a documentation source.
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Open any chat or composer panel
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Type @Docs and select "Add new doc"
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Paste the URL: https://haystack.deepset.ai/llms.txt
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Wait for the green dot (indexing complete)
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Reference @Docs in chat when asking about Haystack
Cursor crawls the URL and indexes all subpages. Add a trailing slash to index child pages too.
Frequently Asked Questions
Haystack publishes its llms.txt at https://haystack.deepset.ai/llms.txt. This file provides a structured, markdown-formatted index of Haystack's documentation that AI systems can consume to understand the project's APIs, guides, and references.
Copy the llms.txt content and paste it into your AI assistant (Cursor, Windsurf, Claude, ChatGPT) as context. This gives the AI an accurate map of Haystack's documentation so it can provide better code suggestions and answers about Haystack.
Haystack's llms.txt contains 3 sections and 16 documentation links in 3.1 KB (~802 tokens). Key sections include Docs, Examples, Optional.
The concise llms.txt index is approximately 802 tokens (3.1 KB). Most AI assistants can fit this within their context window. For the full expanded documentation, look for an llms-full.txt variant which embeds all content inline.
Haystack is an end-to-end framework for building powerful and production-ready AI applications with Large Language Models (LLMs). It enables developers to create custom pipelines for agents, retrieval-augmented generation (RAG), question answering (QA), semantic document search, and more. Haystack's modular architecture allows integration of various technologies from Amazon Bedrock, Langfuse, Qdrant, Elasticsearch, Pgvector, Hugging Face Transformers, and more.. Haystack's llms.txt file helps AI systems understand this by providing a structured overview of its documentation, making it easier for developers to get accurate AI-assisted help when working with Haystack.
Yes. Use the free llms.txt generator at mdream.dev/tools/llms-txt/generator to crawl your site and produce a spec-compliant llms.txt file. You can also validate existing files with the llms.txt validator.