NisaarAgharia/Advanced_RAG
Advanced Retrieval-Augmented Generation (RAG) through practical notebooks, using the power of the Langchain, OpenAI GPTs ,META LLAMA3 ,Agents.
This project offers practical guides for developers to build sophisticated conversational AI systems. It takes raw text data and user queries, then outputs more accurate, contextually rich responses from large language models. This is ideal for AI developers and engineers looking to build advanced RAG-powered applications.
454 stars. No commits in the last 6 months.
Use this if you are a developer looking to integrate advanced Retrieval-Augmented Generation (RAG) techniques into your language model applications to improve accuracy and context.
Not ideal if you are a non-technical user seeking a ready-to-use application, as this project provides development notebooks rather than a finished product.
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454
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84
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Jupyter Notebook
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Last pushed
Apr 26, 2024
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