Use Cases Guides

The following guides are provided to serve as examples for how you can use LangSmith's tracing capabilities to answer common questions about your application. These are not meant to be exhaustive, nor are they optimized for your use case. They are meant as a reference to help you get started.

📄️ Monitor application sentiment

In this guide, you will use create an evaluator to predict the sentiment of user queries in your production application. This technique can be flexibly applied to traced runs to add additional measurements to your unstructured data.

📄️ Summarize app usage

Most usage of LLM applications is in the form of unstructured data. LangChain can be used to

📄️ Few-shot prompting with LangSmith datasets

Datasets are useful for more than just testing, evaluation, and fine-tuning. They can also be used to curate examples for few-shot "learning."