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Key terms

h2oGPTe uses several key terms across its documentation, and each, in turn, is explained on this page.


A Collection refers to a group of related documents.

Enterprise h2oGPTe supports Retrieval Augmented Generation (RAG) when getting responses from an LLM, which allows for contextualizing the question to the LLM with information from documents, audio transcriptions, and other data. Users can create one or more collections of data that they want to get answers about or generate new content from. When a user interacts with an LLM, the user’s prompt is compared with the collection of documents to find similar chunks of information. This information is then sent to the LLM.

There are many strategies for importing and creating collections so that you get the best responses for your use case. For more information, see Collections usage overview.


A Job in Enterprise h2oGPTe signifies a single/batch of crawling or indexing tasks. In particular, the following tasks are referred to as a Job:

  • Ingest a Document from the file system
  • Ingest (add) a Document from upload
  • Ingest (crawl) a website
  • Index Document(s)
  • Update a Collection's statistics
  • Delete a Document(s)
  • Delete a Document(s) from a Collection
  • Delete a Collection(s)
  • Import a stored Document to a Collection
  • Import all Document(s) from a Collection to another Collection
  • Summarize a Document


A Document refers to one of your imported files to h2oGPTe (for example, a PDF or web page).


A Chat refers to questions asked to a Collection in h2oGPTe.

Chatting with a Collection lets you ask h2oGPTe questions about the Document(s) in the Collection. When you ask a question about the Document(s), h2oGPTe crawls through the indexed Document(s) in the Collection to find relevant content to answer the question while utilizing the H2O LLM to summarize a concise question response.


An application programming interface (API) key is a unique identifier to authenticate to the h2oGPTe API.