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Evaluating LLM Applications Using LangChain

Evaluating LLM Applications Using LangChain

Hands-On LangChain for LLM Application Development

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Youssef Hosni
May 11, 2024
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When constructing a sophisticated application employing an LLM, a crucial yet challenging aspect revolves around evaluating its performance. How can you ascertain if it meets accuracy standards? 

Moreover, if you opt to alter your implementation — perhaps by substituting a different LLM or adjusting the strategy for utilizing a vector database or other retrieval mechanisms — how can you gauge whether these changes enhance or detract from the application?

This article discusses the challenges of evaluating the performance of applications built with large language models (LLMs) and explores strategies for effectively assessing their accuracy and effectiveness.

It emphasizes the importance of understanding the inputs and outputs of each step in the application’s workflow and introduces frameworks and tools designed to aid in evaluation. 

Additionally, it explores the concept of using language models and chains themselves to evaluate other models and applications. With the rise of prompt-based development and the growing reliance on LLMs, the process of evaluating application workflows is undergoing reevaluation.

Table of Contents:

  1. Setting Up Working Environment 

  2. Manual Evaluation & Debugging

  3. LLM-Assisted Evaluation

  4. Observing Behind the Scenes


My E-book: Data Science Portfolio for Success Is Out!

Youssef Hosni
·
September 15, 2023
My E-book: Data Science Portfolio for Success Is Out!

I recently published my first e-book Data Science Portfolio for Success which is a practical guide on how to build your data science portfolio. The book covers the following topics: The Importance of Having a Portfolio as a Data Scientist How to Build a Data Science Portfolio That Will Land You a Job?

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