Llama_index

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LlamaIndex is an AI Agents & Automation tool that provides a data framework for building LLM applications. It offers data connectors, data structuring, and an advanced retrieval/query interface to augment LLMs with private data.

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At a glance

Pricing

Open Source

Free tier

Yes

API

Yes

Skill level

Technical

About

What is llama_index?

LlamaIndex is an open-source framework designed to help developers build agentic applications by augmenting Large Language Models (LLMs) with private data. It offers data connectors to ingest various data sources and formats like APIs, PDFs, and SQL databases. The framework provides methods to structure data using indices and graphs, making it easily consumable by LLMs. LlamaIndex also features an advanced retrieval and query interface, allowing users to feed LLM input prompts and receive knowledge-augmented outputs. It integrates seamlessly with other application frameworks such as LangChain, Flask, Docker, and ChatGPT. The platform caters to both beginners with a high-level API for quick data ingestion and querying, and advanced users who can customize and extend any module, including data connectors, indices, and query engines.

Best used for

Ideal for developers and data scientists who need to build LLM applications, integrate diverse data sources, and structure private data for efficient querying. Especially valuable for creating agentic applications and document agents that require advanced retrieval and knowledge augmentation capabilities.

Common actions

build LLM applications

integrate data sources

structure data for LLMs

query private data

customize AI modules

github copilot"AI Agents"face swappingcollaborationlow-code/no-codeautomated workflowopen-sourceworkflowsdeepfake

Capabilities

Key features

Data connectors
Data structuring (indices/graphs)
Advanced retrieval/query interface
Module customization
Integration with frameworks
Agentic OCR

Target Audience

developerdata scientiststartup founder

Integrations

langchainflaskdockerchatgptopenaiollamahuggingface

Pricing & Plans

Open Source

Free

FAQs

What is the difference between `llama-index` and `llama-index-core`?

`llama-index` is a starter Python package that includes the core LlamaIndex framework and a selection of integrations. `llama-index-core` is the foundational package, allowing users to install it and then add specific integration packages from LlamaHub as needed for their application.

Can LlamaIndex be used with non-OpenAI LLMs?

Yes, LlamaIndex is designed to be flexible and supports integration with various LLMs beyond OpenAI. Examples provided in the documentation demonstrate its use with models hosted through Ollama and embedding models from HuggingFace, allowing for diverse LLM choices.

How can I persist and reload an index created with LlamaIndex?

By default, data is stored in-memory. To persist an index, you can use `index.storage_context.persist()` which saves it to disk (under `./storage` by default). To reload, you can use `StorageContext.from_defaults(persist_dir="./storage")` and then `load_index_from_storage(storage_context)`.

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