LangChain just launched their new "LangSmith" platform
LangChain, a leading platform for large language model applications, has just announced the launch of their new platform called LangSmith. This platform is a game-changer for developers looking to take their language model prototypes and put them into production. In this blog post, we will delve into what LangSmith is, why it exists, how you can use it, and what you can actually do with it.
Who is LangSmith For?
LangChain exists to make it as easy as possible to develop large language model powered applications. If you want to go beyond just playing around with these models and actually put them into production, then LangSmith is the platform for you. Whether you want to create applications for your own company, sell them as a service, or offer them to potential clients, LangSmith can help you close the gap between prototype and production.
If this sounds like you, make sure to like this video and subscribe to the channel as we delve further into LangSmith and its capabilities. While the platform is currently in closed beta, you can sign up on the website and join the waitlist to be notified when access becomes available. In the meantime, let's explore what we already know about LangSmith.
What Can LangSmith Do for You?
LangSmith is a platform designed to help developers overcome the challenges of going from prototype to production with their language model applications. One of the main issues developers face is the stochastic and non-deterministic nature of large language models. Every time you query the model, you can get a slightly different result. This introduces ambiguity, especially when user input is involved.
LangSmith addresses this challenge by providing a robust logging system for your runs. It allows you to visualize the steps taken by the model, the number of tokens used, and even provides reference outputs for evaluation purposes. This logging system is invaluable for monitoring the quality and performance of your applications and ensuring that the results align with your expectations.
Additionally, LangSmith offers a playground for experimenting with prompts and tweaking them to achieve the desired output. This feature allows developers to fine-tune their applications and improve their accuracy. Furthermore, LangSmith enables you to share your work with others and create data sets for testing and evaluation, enhancing the collaborative potential of the platform.
A Real-World Example
To illustrate the benefits of LangSmith, let's consider a recent project showcasing a language model application built with LangChain. In this project, a simple language model was used along with SERP API and a math tool to answer questions about median salaries. When running the application, the output can vary due to the non-deterministic nature of language models.
With LangSmith, developers can log their runs and track important information such as the steps taken, token usage, and API costs. This logging system allows for accurate monitoring and evaluation, ensuring that the application is performing as expected. In addition, LangSmith provides visualization capabilities, allowing developers to drill down into each step of the model's reasoning process, making it easier to identify and resolve any issues that arise.
Unlocking the Potential of Language Models with LangSmith
The launch of LangSmith comes at an opportune time for developers, like me, who are transitioning from proof of concept to production with their language model applications. LangSmith offers a unified platform that addresses the challenges of debugging, testing, evaluating, and monitoring these applications.
If you're interested in taking your language model prototypes to the next level and want to learn more about the best practices and insights I have gained from building these applications, make sure to subscribe to my newsletter. In the newsletter, I share tips, stories, and experiences from working with large language models, as well as insights from my collaboration with data professionals worldwide.
LangSmith is set to revolutionize the way we develop and deploy language model applications. With its powerful logging system, visualization capabilities, experimentation playground, and evaluation models, LangSmith provides the tools needed to create robust and reliable applications that users and companies can rely on.
Frequently Asked Questions
1. How can I access LangSmith?
LangSmith is currently in closed beta, but you can sign up on the website and join the waitlist to be notified when access becomes available.
2. Can I use LangSmith for personal projects?
Absolutely! LangSmith is designed to help developers, whether they are working on personal projects or creating applications for their companies or clients.
3. Is LangSmith suitable for all types of language models?
Yes, LangSmith is a versatile platform that can be used with a wide range of large language models. It provides the necessary tools for debugging, testing, and evaluating any language model application.
4. Can I collaborate with others using LangSmith?
While LangSmith is currently in the process of building out a team feature, you can still share your work with others by using the platform's sharing functionality.
5. How can LangSmith help me monitor and evaluate my language model applications?
LangSmith's logging system allows you to track important metrics such as steps taken, token usage, and API costs. Additionally, the platform provides visualization capabilities and evaluation models, enabling you to assess the performance and quality of your applications.
In conclusion, LangSmith is a game-changing platform for developers looking to take their language model prototypes to production. With its robust logging system, visualization capabilities, and evaluation models, LangSmith provides the necessary tools to create reliable and high-performing language model applications. Sign up for early access and take your language model applications to the next level!
