[Shivam Sharma (ShivamSharma43)]

Description

Fixes #3605.

validate_temperature and validate_top_p checked value < low or value > high. Every comparison with NaN is False, so a NaN temperature or top_p passed validation. OpenAIChatTarget, OpenAIResponseTarget, OpenAICompletionTarget, LiteLLMChatTarget and AzureMLChatTarget then stored it in their identifier, and every send failed when httpx encoded the request body (Out of range float values are not JSON compliant).

Changes:

• Both checks now use not 0 <= value <= high, the same form as validate_presence_penalty and validate_frequency_penalty. NaN is rejected with the existing range message. inf and -inf were already rejected, and finite values behave as before.
• The docstrings mention NaN.

Tests and Documentation

• tests/unit/prompt_target/test_target_utils.py: nan, inf and -inf cases for both validators, matching the existing penalty tests. The two nan cases fail on main; the inf cases already passed and document the current behavior.
• pytest tests/unit/prompt_target -k "temperature or top_p or validat or init": 319 passed, 15 skipped.
• ruff check, ruff format and ty check pass on the changed files.
• No documentation changes beyond the docstrings.

🤖 Generated with Claude Code

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[Richard Lundeen (richlundeen)]

The chained bounds checks reject NaN and infinity while preserving None and the inclusive limits. The focused regression cases cover both validators.

No blocking issues found by code inspection. Tests were not run for this review. AI-assisted review (GitHub Copilot).

[Shivam Sharma (ShivamSharma43)]

The only failing job here is test_hierarchy_traversal_halts_immediately_on_budget_exhaustion, the wall-clock timing test reported in #3608, which fails on other PRs too; #3609 makes it deterministic. Roman Lutz (@romanlutz), could you rerun the failed jobs when you have a moment? #3556 and #3592 went green on a rerun.