- Introduce FactCheckingEvaluator class for LLM response validation
- Implement evaluation logic using ChatClient for fact-checking
- Add comprehensive JavaDoc explaining the evaluator's purpose and usage
- Reference Bespoke-Minicheck model for efficient implementation options
- Include links to Ollama blog post and MiniCheck research paper
- Distinguish from 'closed book' scenario testing in documentation
This new evaluator enables detection and reduction of hallucinations
in LLM outputs by checking claims against provided context. It provides
a foundation for implementing advanced fact-checking methodologies in
Spring AI applications.
See https://ollama.com/blog/reduce-hallucinations-with-bespoke-minicheck
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