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Building AI Agents with LLMs
Large language models are the reasoning units behind business-ready AI agents. Learn how they drive decisions and actions in a Compound AI system
By
The deepset Team
More than Metrics: How to Test an NLP System
Our guide to evaluating applications that extract or generate natural language
AI Best Practices
AI Fundamentals
How to Build a Semantic Search Engine in Python
Search your large collection of documents in the most effective way using open source tools
AI Fundamentals
The Beginner’s Guide to Text Embeddings
Text embeddings represent human language to computers, enabling tasks like semantic search. Here, we introduce sparse and dense vectors in a non-technical way.
AI Fundamentals
When and How to Train Your Own Language Model
You’ll almost never have to train a language model from scratch
AI Fundamentals
What Is a Language Model?
What are they used for? Where can you find them? And what kind of information do they actually store?
AI Fundamentals
How to Evaluate a Question Answering System
Introducing the new, simpler way of evaluating extractive QA pipelines in Haystack
AI Best Practices
Question Answering on Structured Data
Learn how to use Haystack NLP framework to extract answers from your tabular data.
AI Architecture
Solutions
Automating Information Extraction with Question Answering
How to use Haystack-based semantic question answering systems to extract information from a collection of financial statements.
