Accelerate LLM App Development with LangSmith Evaluations: RAG Evaluation (Answer Correctness)

 

Evaluations are a crucial step in developing Language Large Models (LLM) applications, but getting started can be daunting. To help you overcome this hurdle, Langchain launched a new video series focused on evaluations in LangSmith.

In their 12th video, dive into RAG (Retrieval Augmented Generation) evaluation, a crucial aspect of ensuring the accuracy of your LLM app. 
With LangSmith, you can:

• Create a dataset of expected answers
• Run an evaluation to compare your output with ground truth reference answers
• Dive into output traces to identify inaccuracies in your responses
  
  

By leveraging LangSmith evaluations, you can accelerate your LLM app development and ensure the highest level of accuracy and reliability. 

Watch the video now and learn how to evaluate your LLM app with LangSmith!