Langchain

What is Langsmith? A Step-by-Step Guide to setup Langsmith

LangSmith helps your team debug, evaluate, and monitor your language models

Langsmith is an application framework for language models equipped with LLM tools and agent support. It focuses on addressing challenges faced during language model development for production. This guide offers an in-depth look into the essential features and functionalities of Langsmith.

Understanding Langsmith vs Langchain

Prior to exploring Langsmith, it is crucial to differentiate between Langsmith and Langchain. While Langchain is mainly used for prototyping, Langsmith is designed to tackle challenges at the production level. Langsmith introduces new features centered around debugging, testing, evaluating, monitoring, and usage metrics.

Key Features of Langsmith

Langsmith provides various features to enhance the development and deployment of language models:

Debugging: Langsmith offers robust debugging capabilities to identify and resolve errors in language models efficiently.
Testing: The framework enables comprehensive testing of language models to ensure accuracy and reliability.
Evaluating: Langsmith includes tools for evaluating language models' performance against predefined metrics.

Setting Up Langsmith: A Step-by-Step Guide

Setting up Langsmith for language model development and deployment requires attention to detail. Follow this step-by-step guide to ensure a seamless setup:

1. Create a Langsmith Account

Start by creating a Langsmith account to access the platform's tools and resources. This will also allow you to generate an API key for authentication and integration purposes.

2. Familiarize Yourself with Langsmith Documentation

Prior to beginning the development process, review the Langsmith documentation to understand the platform's features, functionalities, and best practices.

3. Configure Your Environment Variables

Set up your environment variables to enable tracing in Langsmith. This can be done by setting the LANGCHAIN_TRACING_V2 environment variable to true and specifying the project to log to by setting the LANGCHAIN_PROJECT environment variable.

4. Log Runs to Langsmith

Once your environment variables are configured, start logging runs to Langsmith. This will allow you to monitor the performance and behavior of your language models, making it easier to implement necessary adjustments and improvements.

5. Seek Support and Feedback

If you encounter challenges or wish to provide feedback on Langsmith, engage with the community through Discord, Twitter, or GitHub. Your input is valuable for enhancing the platform and meeting user needs.

References
https://github.com/langchain-ai/langsmith-sdk
https://www.langchain.com/langsmith
https://python.langchain.com/docs/langsmith/walkthrough