LlamaIndex
LlamaIndex is a tool for building indexes and querying local documents, which acts as a bridge between custom data and large language models (LLMs). It allows users to retrieve relevant information from local documents and provide more reliable answers. The design goal of LlamaIndex is to leverage the power of large language models by operating on specified data in order to obtain the required information when answering questions or performing other tasks.
LlamaIndex was originally called GPT Index, and was later renamed LlamaIndex as large language models developed rapidly. It provides a set of tools to create a knowledge base, including data connectors (for ingesting data from different sources and formats), documents/nodes (as containers and fragments of data), data indexing (the process of organizing into a retrievable format), and other components.
LlamaIndex was developed by Cohere and was first made public in version 0.5.17.post1 before May 1, 2023.
It helps users communicate with intelligent machines through the following key functions:
- Data Ingestion: Get data from its original source into the system.
- Data structuring: Organize the data in a way that is easy for language models to understand.
- Data Retrieval: Find and get the right data when you need it.
- Simplify integration: It is easier to integrate data with various application frameworks.
Core Components of LlamaIndex
- knowledge base: Stores useful information, such as FAQ, manuals and other documents.
- Trigger/Query: A question or request from a user that triggers the system to take action.