nsrinidhibhat/gradio_RAG

Code and resources showcasing the Retrieval-Augmented Generation (RAG) technique, a solution for enhancing data freshness in Large Language Models (LLMs). Incorporate up-to-date external knowledge into LLM-generated responses. Additionally, this repository includes a Gradio-based user interface for seamless model deployment.

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This project helps you create a smart chatbot that can answer questions using the very latest information, even if the underlying AI model isn't up-to-date. You provide documents (like PDFs or CSVs) as a knowledge base, and the chatbot uses this information to generate accurate, current responses to user queries. This is ideal for anyone who needs to build a question-answering system that relies on fresh, domain-specific information, such as content creators, researchers, or customer support specialists.

No commits in the last 6 months.

Use this if you need to build a chatbot or question-answering system that incorporates the most recent information from your own documents, rather than relying solely on an AI model's potentially outdated training data.

Not ideal if you are looking for a pre-built, production-ready chatbot without needing to provide your own external data or customize the underlying AI models.

knowledge-management chatbot-development information-retrieval content-generation customer-support
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 8 / 25
Maturity 8 / 25
Community 18 / 25

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Language

Python

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Last pushed

Aug 22, 2023

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