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.

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/ 100
Emerging

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.

No commits in the last 6 months.

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.

MLOps chatbot-development Azure-Databricks AI-deployment LLM-operations
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 5 / 25
Maturity 16 / 25
Community 17 / 25

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Stars

10

Forks

8

Language

License

Category

rag-applications

Last pushed

May 17, 2024

Commits (30d)

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