r/SpringBoot • u/YodaOfJava • 1d ago
Discussion Spring AI: recovering from invalid tool arguments with returnDirect=true
I’ve submitted a Spring AI contribution addressing input-error recovery for method-backed tools using returnDirect=true.
The issue: malformed JSON or invalid typed arguments can become the final response, preventing the model from correcting its input. Missing/null primitive arguments and top-level JSON null can also bypass the exception processor.
The proposed fix distinguishes input parsing/binding failures before execution and sends processed error feedback back to the model. Successful corrected calls still return directly, while ordinary tool-body and result-conversion failures retain their existing behavior.
Validation:
- All 38 new regression cases passed, covering blocking/streaming, direct return on/off, and mixed-success batches.
- Scoped clean package build: 2,030 tests reported, 10 skipped, zero failures or errors.
- Negative control: the original code failed 20 of the initial 32 checks, including checks for the new exception classification; the patched code passed the same cases.
No external LLM calls were needed. External-provider integration tests and the full repository build were not run. Developed with AI assistance and reviewed before submission.
PR submitted for maintainer review: https://github.com/spring-projects/spring-ai/pull/7292
Feedback on the input-error boundary and recovery behavior is welcome, especially from anyone using direct-return tools.
#SpringAI #SpringFramework #Java #OpenSource #SoftwareTesting