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Components that dynamically select the most appropriate tool or data source to process a specific user query.
Distinguishing note: Focuses on the routing logic layer of RAG systems, distinct from general retrieval or orchestration.
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LlamaIndex is a comprehensive development framework designed to connect private or external data sources to large language models. It functions as a data-centric toolkit that enables the construction of retrieval-augmented generation systems, allowing developers to build applications that provide context-aware answers based on specific organizational information. The project distinguishes itself through a robust agentic orchestration engine that supports the creation of autonomous agents capable of multi-step reasoning, memory management, and complex tool execution. Beyond simple retrieval, i
LlamaIndex composes multiple query engines into a single router that dynamically selects the most relevant tool to process a user query based on provided descriptions.