GPT Index is a project consisting of a set of data structures designed to make it easier to use large external knowledge bases with LLMs.
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🗂️ ️GPT Index

GPT Index is a project consisting of a set of data structures designed to make it easier to use large external knowledge bases with LLMs.

PyPi: https://pypi.org/project/gpt-index/.

Documentation: https://gpt-index.readthedocs.io/en/latest/.

Twitter: https://twitter.com/gpt_index.

Discord: https://discord.gg/dGcwcsnxhU.

🚀 Overview

NOTE: This README is not updated as frequently as the documentation. Please check out the documentation above for the latest updates!

Context

  • LLMs are a phenomenonal piece of technology for knowledge generation and reasoning.
  • A big limitation of LLMs is context size (e.g. Davinci's limit is 4096 tokens. Large, but not infinite).
  • The ability to feed "knowledge" to LLMs is restricted to this limited prompt size and model weights.

Proposed Solution

At its core, GPT Index contains a toolkit of index data structures designed to easily connect LLM's with your external data. GPT Index helps to provide the following advantages:

  • Remove concerns over prompt size limitations.
  • Abstract common usage patterns to reduce boilerplate code in your LLM app.
  • Provide data connectors to your common data sources (Google Docs, Slack, etc.).
  • Provide cost transparency + tools that reduce cost while increasing performance.

Each data structure offers distinct use cases and a variety of customizable parameters. These indices can then be queried in a general purpose manner, in order to achieve any task that you would typically achieve with an LLM:

  • Question-Answering
  • Summarization
  • Text Generation (Stories, TODO's, emails, etc.)
  • and more!

💡 Contributing

Interesting in contributing? See our Contribution Guide for more details.

📄 Documentation

Full documentation can be found here: https://gpt-index.readthedocs.io/en/latest/.

Please check it out for the most up-to-date tutorials, how-to guides, references, and other resources!

💻 Example Usage

pip install gpt-index

Examples are in the examples folder. Indices are in the indices folder (see list of indices below).

To build a simple vector store index:

from gpt_index import GPTSimpleVectorIndex, SimpleDirectoryReader
documents = SimpleDirectoryReader('data').load_data()
index = GPTSimpleVectorIndex(documents)

To save to and load from disk:

# save to disk
index.save_to_disk('index.json')
# load from disk
index = GPTSimpleVectorIndex.load_from_disk('index.json')

To query:

index.query("<question_text>?")

🔧 Dependencies

The main third-party package requirements are tiktoken, openai, and langchain.

All requirements should be contained within the setup.py file. To run the package locally without building the wheel, simply run pip install -r requirements.txt.

📖 Citation

Reference to cite if you use GPT Index in a paper:

@software{Liu_GPT_Index_2022,
author = {Liu, Jerry},
doi = {10.5281/zenodo.1234},
month = {11},
title = {{GPT Index}},
url = {https://github.com/jerryjliu/gpt_index},year = {2022}
}

Contributors

jerryjliu
ravi03071991
emptycrown
bborn
hongyishi
eltociear
teoh
hwchase17
veered
MistApproach
Disiok
VivaLaPanda
kahkeng
adamcohenhillel
alec-tschantz
aliyeysides
cwelton
cclauss
cry-stal-lee
davidtsong
EthanBlackburn
hursh-desai
ihfazhillah
Haowjy
ephe-meral
JohnShahawy
cnrpman
kacperlukawski
kevinqz
pavanyellow
mmz-001
PandaWhoCodes
vguillet
Zeyuzhao
ddrling
gwpx
mattbarron
tigsss