llama.cpp server now accepts null sampling parameters

The open-source llama.cpp project, known for running large language models locally, just merged commit b9967 which improves its server's handling of sampling parameters. Previously, sending a null value for fields like temperature or top_p could cause issues; now the server treats null as if the parameter was omitted entirely, defaulting to the server's configured values. This matches the OpenAI API specification where null on optional parameters means 'use default', making it easier for developers to build clients that work across both OpenAI's hosted models and local llama.cpp instances.

The implementation adds a `has_value()` function to skip null checks in the field evaluation guards, extending the existing `json_value` convention. This is a small but meaningful quality-of-life improvement for the 120k+ stars project, reducing edge cases and simplifying integration for AI tooling that sends partial parameter sets. The change was verified and signed, and is now part of the main branch as of July 10.