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🗂️ ️GPT Index

GPT Index is a project consisting of a set of data structures that are created using LLMs and can be traversed using LLMs in order to answer queries.

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

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

🚀 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 phenomenal piece of technology for knowledge generation and reasoning.
  • A big limitation of LLMs is context size (e.g. OpenAI's davinci model for GPT-3 has a limit of 4096 tokens. Large, but not infinite).
  • The ability to feed "knowledge" to LLMs is restricted to this limited prompt size and model weights.
  • Thought: what if LLMs could have access to potentially a much larger database of knowledge without retraining/finetuning?

Proposed Solution

That's where GPT Index comes in. GPT Index is a simple, flexible interface between your external data and LLMs. It resolves the following pain points:

  • Provides simple data structures to resolve prompt size limitations.
  • Offers data connectors to your external data sources.
  • Offers you a comprehensive toolset trading off cost and performance.

At the core of GPT Index is a data structure. Instead of relying on world knowledge encoded in model weights, a GPT Index data structure does the following:

  • Uses a pre-trained LLM primarily for reasoning/summarization instead of prior knowledge.
  • Takes a large corpus of text data as input and builds a structured index over it (using an LLM or heuristics).
  • Allow users to query the index in order to synthesize an answer to the question - this requires both traversal of the index as well as a synthesis of the answer.

💡 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 tree index:

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

To save to and load from disk:

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

To query:

index.query("<question_text>?", child_branch_factor=1)

🔧 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.