Apply filter_overlong_prompts in multiturn rollout setting

[HwCARI]

What does this PR do?

Fixes #2069.

filter_overlong_prompts was silently skipped in the multiturn setting in verl/verl/experimental/agent_loop/tool_agent_loop.py, causing prompts exceeding data.max_prompt_length to pass through unfiltered. This resulted in tensor size mismatches downstream when batching sequences:

RuntimeError: Sizes of tensors must match except in dimension 0.
Expected size 2048 but got size 2106 for tensor number 2 in the list.

This PR ensures the overlong prompt filter is applied consistently regardless of whether multiturn tool use is enabled.

Fix

Apply filter_overlong_prompts in verl/verl/experimental/agent_loop/tool_agent_loop.py.

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[gemini-code-assist]

Code Review

This pull request introduces prompt truncation logic to the ToolAgentLoop to handle long prompts and prevent crashes. Feedback highlights that self.rollout_config.prompt_length should be used as the truncation limit for consistency with the rollout pipeline. A bug was also identified where an undefined variable self.max_prompt_length would cause an AttributeError. Furthermore, the truncation logic should be extended to cover multi-turn conversation history to ensure the prompt remains within bounds throughout the interaction.

[HwCARI]

@wuxibin89 and @ArronHZG, Could you please review this PR? Thanks