Starter Tutorial

Here is a starter example for using LlamaIndex. Make sure you’ve followed the installation steps first.


LlamaIndex examples can be found in the examples folder of the LlamaIndex repository. We first want to download this examples folder. An easy way to do this is to just clone the repo:

$ git clone

Next, navigate to your newly-cloned repository, and verify the contents:

$ cd llama_index
$ ls
LICENSE                data_requirements.txt  tests/            examples/              pyproject.toml
Makefile               experimental/          requirements.txt              llama_index/   

We now want to navigate to the following folder:

$ cd examples/paul_graham_essay

This contains LlamaIndex examples around Paul Graham’s essay, β€œWhat I Worked On”. A comprehensive set of examples are already provided in TestEssay.ipynb. For the purposes of this tutorial, we can focus on a simple example of getting LlamaIndex up and running.

Build and Query Index

Create a new .py file with the following:

from llama_index import VectorStoreIndex, SimpleDirectoryReader

documents = SimpleDirectoryReader('data').load_data()
index = VectorStoreIndex.from_documents(documents)

This builds an index over the documents in the data folder (which in this case just consists of the essay text). We then run the following

query_engine = index.as_query_engine()
response = query_engine.query("What did the author do growing up?")

You should get back a response similar to the following: The author wrote short stories and tried to program on an IBM 1401.

Viewing Queries and Events Using Logging

In a Jupyter notebook, you can view info and/or debugging logging using the following snippet:

import logging
import sys

logging.basicConfig(stream=sys.stdout, level=logging.DEBUG)

You can set the level to DEBUG for verbose output, or use level=logging.INFO for less.

Saving and Loading

By default, data is stored in-memory. To persist to disk (under ./storage):


To reload from disk:

from llama_index import StorageContext, load_index_from_storage

# rebuild storage context
storage_context = StorageContext.from_defaults(persist_dir="./storage")
# load index
index = load_index_from_storage(storage_context)

Next Steps

That’s it! For more information on LlamaIndex features, please check out the numerous β€œGuides” to the left. If you are interested in further exploring how LlamaIndex works, check out our Primer Guide.

Additionally, if you would like to play around with Example Notebooks, check out this link.