LakshitaS/Agentic-RAG-implementation
Implementation of "Building Agentic RAG with LlamaIndex" offered by DeepLearning.AI focusing on developing intelligent research agents using the Retrieval-Augmented Generation (RAG) framework.
This project helps developers build intelligent research agents capable of understanding and responding to complex queries. It takes in user questions and various document sources, then outputs synthesized answers by routing queries to appropriate tools, calling external functions, and performing multi-step reasoning. Python developers, AI engineers, and data scientists looking to implement sophisticated RAG systems would use this.
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Use this if you are a developer looking to build a multi-step AI research assistant that can intelligently process information across multiple documents.
Not ideal if you are an end-user seeking a ready-to-use AI tool rather than a framework for building one.
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Jun 25, 2024
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