Building an AI agent with OpenAPI: LangChain vs. Haystack

The blog post explores the development of AI agents using OpenAPI with two popular frameworks, LangChain and Haystack, to assist in processing user queries and interacting with APIs. Both frameworks are evaluated by building an AI agent for querying a mock Formula One (F1) API. LangChain offers flexibility and an extensive community but suffers from outdated documentation and reliance on community-driven modules, which can lead to deprecation challenges and the need for extensive debugging. Haystack, initially designed for search and question-answering, provides a more standardized pipeline structure with accurate, up-to-date documentation, resulting in a more straightforward setup and reliable operation. The post highlights the strengths and weaknesses of each framework, including their handling of agent hallucinations and debugging processes, and concludes that while LangChain offers more flexibility for experimental projects, Haystack is better suited for production-level systems due to its stability and comprehensive documentation.