Generate input test cases.
Synthetic input generation allows you to create test questions from descriptions and examples. This helps expand test coverage and evaluate how your AI system handles different types of queries. You can use this to:
You can generate example inputs specific to your LLM app context.
In the Evidently UI, start a new Project or open an existing one.
Define what kind of inputs you need by providing a brief description of the task and choose how many inputs to generate. For example, if you’re building a travel assistant, you could enter:
This guides the system in generating relevant and diverse inputs. You can also use a more detailed prompt:
The system will generate a list of input questions based on your description. You can preview and refine the generated dataset.
You can:
Once finalized, save the dataset. You can download it as a CSV file or access it via the Python API using the dataset ID.
Dataset API. How to work with Evidently datasets.
Generate input test cases.
Synthetic input generation allows you to create test questions from descriptions and examples. This helps expand test coverage and evaluate how your AI system handles different types of queries. You can use this to:
You can generate example inputs specific to your LLM app context.
In the Evidently UI, start a new Project or open an existing one.
Define what kind of inputs you need by providing a brief description of the task and choose how many inputs to generate. For example, if you’re building a travel assistant, you could enter:
This guides the system in generating relevant and diverse inputs. You can also use a more detailed prompt:
The system will generate a list of input questions based on your description. You can preview and refine the generated dataset.
You can:
Once finalized, save the dataset. You can download it as a CSV file or access it via the Python API using the dataset ID.
Dataset API. How to work with Evidently datasets.