text: longer documents. A type of Data-Augmented Generation.        - [Evaluation](https://python.langchain.com/en/latest/use_cases/evaluation.html): Generative models are hard to evaluate with traditional metrics. One promising approach is to use language models themselves to do the evaluation.            ## Reference Docs [\#](\#reference-docs "Permalink to this headline")        Full documentation on all methods, classes, installation methods, and integration setups for LangChain.        - [Reference Documentation](https://python.langchain.com/en/latest/reference.html)            ## LangChain Ecosystem [\#](\#langchain-ecosystem "Permalink to this headline")        Guides for how other companies/products can be used with LangChain.        - [LangChain Ecosystem](https://python.langchain.com/en/latest/ecosystem.html)            ## Additional Resources [\#](\#additional-resources "Permalink to this headline")        Additional resources we think may be useful as you develop your application!        - [LangChainHub](https://github.com/hwchase17/langchain-hub): The LangChainHub is a place to share and explore other prompts, chains, and agents.        - [Gallery](https://python.langchain.com/en/latest/additional_resources/gallery.html): A collection of our favorite projects that use LangChain. Useful for finding inspiration or seeing how things were done in other applications.        - [Deployments](https://python.langchain.com/en/latest/additional_resources/deployments.html): A collection of instructions, code snippets, and