langfuse-dataset-setup

To set up Langfuse datasets, you need to define the dataset purpose, evaluation dimensions, score configurations, and judge prompts. This process structures your data for both LLM-as-judge and human review workflows.

Yes, you can configure LLM-as-judge evaluations by generating specific judge prompts using provided templates. The setup supports defining evaluation metrics such as accuracy, helpfulness, and relevance to score responses.

The best way to define evaluation dimensions is to outline specific metrics like accuracy and relevance during dataset creation. Configuring score types and judge prompts ensures structured prompt engineering evaluation.

Yes, generating judge prompts for human review utilizes specific templates provided during the evaluation configuration. These templates guide the setup of score types and prompt structures for your data management workflow.

Yes, Langfuse dataset setup supports custom score configurations for evaluating chatbot accuracy. It guides you through defining the dataset purpose and configuring the necessary scoring metrics for your evaluations.