{"categories":[{"label":"Python Modules","url":"https://skillfed.io/packages/category/software-development-libraries-python-modules/4"},{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/2"},{"label":"Application Frameworks","url":"https://skillfed.io/packages/category/software-development-libraries-application-frameworks"}],"enrichment":{"capability":"LlamaIndex is a data framework that connects large language models to your own data sources, enabling retrieval-augmented generation (RAG) and agentic applications through data connectors, indexing, and query interfaces.","skillfed_tags":["rag-framework","llm-integration","data-indexing"],"use_cases":["Build a chatbot that answers questions about your company's internal documentation or knowledge base.","Create a semantic search system over a large collection of PDFs, research papers, or legal documents.","Develop an agentic application that retrieves and reasons over structured and unstructured data.","Index and query data from multiple sources (APIs, databases, files) with a unified interface.","Prototype a retrieval-augmented generation (RAG) pipeline without managing vector databases directly."],"what_it_does":"LlamaIndex is a data framework designed to bridge the gap between large language models and private or custom data sources. It provides data connectors to ingest various formats (APIs, PDFs, SQL databases, etc.), structures that data into indices and graphs, and retrieval interfaces that augment LLM prompts with relevant context. The framework supports both high-level APIs for quick prototyping and lower-level customization for advanced use cases.\n\nThe package ships with integrations for llama-index-embeddings-openai and llama-index-llms-openai out of the box, and can be extended with additional integration packages for different LLM providers, embedding models, and vector stores. It handles the full pipeline from document ingestion through indexing to query execution, with built-in support for persistence and reloading from disk.","worth_installing":"Yes. LlamaIndex is actively maintained with low install friction, permissive MIT licensing, and no known vulnerabilities. It is well-suited for developers building LLM applications that need to augment models with private data. Start here if you want a batteries-included RAG framework; use llama-index-core if you prefer to assemble integrations \u00e0 la carte."},"id":"llama-index","links":{"html":"https://skillfed.io/packages/llama-index","md":"https://skillfed.io/packages/llama-index.md","pypi":"https://pypi.org/project/llama-index/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-06-24","license_spdx":"MIT","license_treatment":"permissive","name":"llama-index","python_support":"supports_current","summary":"Interface between LLMs and your data"},"popularity":{"monthly_downloads":7378605,"position":1747,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"0.14.23"}