Skip to content


One of the most common use-cases for an LLM application is to answer questions about a set of documents. LlamaIndex has rich support for many forms of question & answering.

Types of question answering use cases#

Q&A has all sorts of sub-types, such as:

What to do#

  • Semantic search: finding data that matches not just your query terms, but your intent and the meaning behind your question. This is sometimes known as "top k" search.
  • Example of semantic search
  • Summarization: condensing a large amount of data into a short summary relevant to your current question
  • Example of summarization
  • Combine multiple sources: is some of your data in Slack, some in PDFs, some in unstructured text? LlamaIndex can combine queries across an arbitrary number of sources and combine them.
  • Example of combining multiple sources
  • Route across multiple sources: given multiple data sources, your application can first pick the best source and then "route" the question to that source.
  • Example of routing across multiple sources
  • Multi-document queries: some questions have partial answers in multiple data sources which need to be questioned separately before they can be combined
  • Example of multi-document queries

Further examples#

For further examples of Q&A use cases, see our Q&A section in Putting it All Together.