{"categories":[{"label":"Python Modules","url":"https://skillfed.io/packages/category/software-development-libraries-python-modules/6"},{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/3"},{"label":"Application Frameworks","url":"https://skillfed.io/packages/category/software-development-libraries-application-frameworks/2"}],"enrichment":{"capability":"LlamaIndex Legacy is a data framework for building LLM applications that connects private data to language models through indexing, retrieval, and query interfaces.","skillfed_tags":["rag-framework","llm-data-integration","vector-indexing"],"use_cases":["Build a chatbot that answers questions about internal documentation or knowledge bases","Create semantic search over large document collections without manual indexing","Augment an LLM with domain-specific data for more accurate contextual responses","Prototype a retrieval-augmented generation pipeline with minimal boilerplate","Index and query structured data from SQL databases alongside unstructured documents"],"what_it_does":"LlamaIndex Legacy is a framework for augmenting language models with private data through structured indexing and retrieval. It sits between your data sources and LLM applications, handling ingestion, structuring into indices, and retrieval-augmented query execution. The package provides both high-level APIs for quick prototyping and lower-level customization points for advanced use cases.\n\nThe framework depends on core data science libraries (SQLAlchemy, pandas, numpy) for data handling, embedding and tokenization (tiktoken, openai), and async utilities (aiohttp, nest-asyncio). It supports multiple LLM backends and embedding providers. Data can be persisted to disk or kept in-memory, and query results are augmented with retrieved context before being sent to the LLM.","worth_installing":"Yes, if you are building an LLM application that needs to incorporate private data and are comfortable with the legacy version status. The package is actively maintained, has no known vulnerabilities, and offers a straightforward API for common retrieval tasks. However, verify whether migration to the current package is recommended for your use case, as this is explicitly a legacy release."},"id":"llama-index-legacy","links":{"html":"https://skillfed.io/packages/llama-index-legacy","md":"https://skillfed.io/packages/llama-index-legacy.md","pypi":"https://pypi.org/project/llama-index-legacy/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2024-11-07","license_spdx":null,"license_treatment":"permissive","name":"llama-index-legacy","python_support":"supports_current","summary":"Interface between LLMs and your data"},"popularity":{"monthly_downloads":2347955,"position":3116,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"0.9.48.post4"}