If you ask an LLM for structured output and validate it against a schema, you already know the...
If you ask an LLM for structured output and validate it against a schema, you already know the failure
mode: most of the time it is fine, and every so often it hands back something that does not parse or
misses a required field. The usual reflex is to wrap the call in a retry and move on.
The problem is that a plain retry is the same prompt, the same temperature, roughly the same odds. You
are paying for another round and hoping the dice land differently.
A validation failure is not an exception to hide. It is a record your system does not yet know how to...
The standard workflow for evaluating LLM output quality goes something like this: someone reads...
Every developer who has worked with LLMs has been there. You ask the model for JSON. You describe the...
A small change that cut our schema-related retries: validate the Pydantic model before sending the...
A few months ago, I noticed something frustrating while building AI applications: The model response...
When TestSmith generates tests with --llm, it calls an LLM for every public member of every source...
