![]() ![]() environ = "YOUR_OPENAI_API_KEY" from llama_index import VectorStoreIndex, SimpleDirectoryReader documents = SimpleDirectoryReader ( "YOUR_DATA_DIRECTORY" ). To build a simple vector store index using OpenAI: import os os. ![]() Indices are in the indices folder (see list of indices below). Please check it out for the most up-to-date tutorials, how-to guides, references, and other resources! □ Example Usage pip install llama-indexĮxamples are in the examples folder. Interested in contributing? See our Contribution Guide for more details. ![]() Our lower-level APIs allow advanced users to customize and extend any module (data connectors, indices, retrievers, query engines, reranking modules), Our high-level API allows beginner users to use LlamaIndex to ingest and query their data inĥ lines of code. LlamaIndex provides tools for both beginner users and advanced users. with LangChain, Flask, Docker, ChatGPT, anything else). Allows easy integrations with your outer application framework (e.g.Provides an advanced retrieval/query interface over your data: Feed in any LLM input prompt, get back retrieved context and knowledge-augmented output.Provides ways to structure your data (indices, graphs) so that this data can be easily used with LLMs.Offers data connectors to ingest your existing data sources and data formats (APIs, PDFs, docs, SQL, etc.).LlamaIndex is a "data framework" to help you build LLM apps. ![]() We need a comprehensive toolkit to help perform this data augmentation for LLMs.
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