microsoft / kernel-memory

RAG architecture: index and query any data using LLM and natural language, track sources, show citations, asynchronous memory patterns.
https://microsoft.github.io/kernel-memory
MIT License
1.35k stars 252 forks source link

Add evaluation root project #501

Closed kbeaugrand closed 1 month ago

kbeaugrand commented 1 month ago

Implementing Evaluation Based on RAGAS Framework

Description

This pull request marks the beginning of our implementation of evaluation metrics for our Retrieval Augmented Generation (RAG) pipelines using the RAGAS framework.

Background

RAGAS (RAG Assessment) is a comprehensive framework designed to evaluate RAG pipelines. RAG pipelines utilize external data to enhance the context provided to Large Language Models (LLMs). While building these pipelines is facilitated by existing tools, evaluating their performance quantitatively remains a challenge. RAGAS addresses this gap by offering tools based on cutting-edge research to evaluate LLM-generated text and provide valuable insights into the effectiveness of RAG pipelines.

Features to be Implemented

The implementation will leverage Kernel Memory to deliver the following evaluation features:

Integration

RAGAS will be integrated into our CI/CD pipeline to enable continuous performance monitoring and evaluation of our RAG pipelines. This integration will ensure that our RAG systems consistently meet the desired performance benchmarks.

Next Steps

dluc commented 1 month ago

Looks like the Release build is broken, maybe something's been removed from the solution?

kbeaugrand commented 1 month ago

Looks like the Release build is broken, maybe something's been removed from the solution?

I'll take a look asap.

dluc commented 1 month ago

Looks like the Release build is broken, maybe something's been removed from the solution?

I'll take a look asap.

no worries I just pushed a fix