Datasets are often used for evaluations, but they can also be exported. Each dataset can be assigned a name for easy search later on.You can create a dataset from your LLM request history or by uploading a dataset file.Datasets are also versioned, allowing you to add examples over time.
Creating a dataset from your history is straightforward using the Dataset dialogue. Here, you can build a dataset from your request history. The dataset will include metadata, input variable context, tags, and the request response. This is useful for backtesting new prompt versions.When creating a dataset from your history, several options are available for customization. You have the option to use time filters to narrow down the history included in the dataset by specifying a start and end time. Additionally, you can refine your dataset by including specific metadata or prompt templates, where metadata involves key-value pairs and prompt templates can be specified by name and version numbers. For those seeking more advanced customization, filtering based on a search query, specific scoring criteria, or tags can be used to build your dataset.
You can also upload a dataset file in CSV or JSONL format. The uploaded file should contain the input variables and any expected outputs you want to include in the dataset.When uploading a dataset, ensure that the file is properly formatted. For CSV files, each column should represent an input variable or expected output, with the first row containing the headers. For JSONL files, each line should be a valid JSON object representing a single example with key-value pairs for input variables and expected outputs.
