Ayush-Patel-10/RAG-using-Azure-Databricks-CI-CD
End-to-end deployment of a scalable RAG chatbot utilizing LangChain for retrieval-based QnA. The project leverages robust CI/CD practices integrating MLFlow with emphasizes on cost analysis.
This project provides an end-to-end framework for deploying a highly accurate, context-aware chatbot on Azure Databricks. It takes your organization's internal documents and turns them into a responsive Q&A system, ensuring the chatbot provides relevant answers while continuously integrating updates. This solution is ideal for MLOps engineers, AI solution architects, or data scientists responsible for building and maintaining enterprise-grade AI applications.
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Use this if you need to deploy a scalable, production-ready RAG-based chatbot on Azure Databricks with robust CI/CD, detailed model tracking, and cost management.
Not ideal if you are looking for a simple, quick-start chatbot solution without the need for enterprise-level MLOps practices or Azure Databricks infrastructure.
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May 17, 2024
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