rag-time and rag-experiment-accelerator

rag-time
53
Established
Maintenance 2/25
Adoption 10/25
Maturity 16/25
Community 25/25
Maintenance 0/25
Adoption 10/25
Maturity 16/25
Community 24/25
Stars: 853
Forks: 308
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: MIT
Stars: 298
Forks: 106
Downloads:
Commits (30d): 0
Language: Python
License:
Stale 6m No Package No Dependents
Stale 6m No Package No Dependents

About rag-time

microsoft/rag-time

RAG Time: A 5-week Learning Journey to Mastering RAG

This project offers a comprehensive, expert-led learning journey to help developers and AI practitioners master Retrieval-Augmented Generation (RAG). It provides step-by-step guides, live coding samples, and expert insights, taking you from foundational concepts to advanced optimization and multimodal RAG techniques. You will learn to build smarter AI applications by understanding how to integrate external knowledge into large language models.

AI development machine learning engineering natural language processing information retrieval large language models

About rag-experiment-accelerator

microsoft/rag-experiment-accelerator

The RAG Experiment Accelerator is a versatile tool designed to expedite and facilitate the process of conducting experiments and evaluations using Azure Cognitive Search and RAG pattern.

This tool helps researchers, data scientists, and developers efficiently test and evaluate the performance of RAG (Retrieval Augmented Generation) systems built with Azure AI Search and Azure OpenAI. You provide your data and search queries, and it produces detailed reports and visualizations comparing how different search strategies and configurations impact the quality of AI-generated responses. It's designed for those who need to fine-tune and optimize their RAG applications.

AI-application-development Generative-AI-evaluation Search-optimization Data-science-experimentation Natural-language-processing

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