[Bug Fix] Fix Camel example training code parameter passing issue

[HwVanICI]

Description

This PR fixes bugs of the Camel example training code. In the run_agent() function of CamelMathAgent class is updated to pass the max_tokens and step_timeout parameter properly as follows.

• Remove the "token_limit" parameter which is not accepted by CamelAgent.
• Create a new "model_config_dict" dictionary including "max_tokens" elememnt, and pass it to the model parameter when creating ChatAgent instance.
• Pass the "step_timeout" parameter when creating a ChatAgent instance. The "step_timeout" parameter is set using the "request_timeout" rollout configuration from yaml file to make it consistent with rollout timeout.
• Added additional rollout configuration in the config.yaml file to set "request_timeout" which can be used to set the "step_timeout".

Related Issue

Fixes #(issue)

Type of Change

• Bug fix (non-breaking change that fixes an issue)
• New feature (non-breaking change that adds functionality)
• Breaking change (fix or feature that would cause existing functionality to not
  work as expected)
• Documentation update
• Code refactoring (no functional changes)
• Performance improvement
• Test coverage improvement

Checklist

• I have read the Contributing Guide
• I have run formatting tools (pre-commit or manual)
• I have run relevant unit tests and they pass
• I have added tests for new functionality
• I have updated documentation if needed
• My branch is up to date with main
• This PR introduces breaking changes (if yes, fill out details below)
• If this PR changes documentation, I have built and previewed it locally with
  jb build docs
• No critical issues raised by AI reviewers (/gemini review)

---

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[gemini-code-assist]

Summary of Changes

Hello @HwVanICI, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request resolves critical bugs within the Camel example training code by refining how agent configuration parameters, specifically max_tokens and step_timeout, are managed. It ensures that these parameters are correctly passed to the ChatAgent and AReaLOpenAICompatibleModel instances, aligning the step_timeout with a newly introduced request_timeout setting in the configuration file. This change improves the robustness and consistency of the agent's behavior during training.

Highlights

• Parameter Handling: Corrected the way max_tokens and step_timeout parameters are passed to CamelAgent and ChatAgent instances, ensuring proper configuration.
• Configuration Update: Introduced a new request_timeout configuration in config.yaml to standardize the step_timeout value across the agent's operations.
• Bug Fix: Addressed bugs in the Camel example training code related to agent parameterization, improving the stability and correctness of the agent's execution.

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[gemini-code-assist]

Code Review

This pull request aims to fix parameter passing for max_tokens and step_timeout in the Camel example. The changes correctly remove the unsupported token_limit parameter and pass max_tokens via the model_config_dict. However, I've found a critical issue where an incorrect attribute name is used to fetch the request timeout, which would cause a runtime error. I've provided a suggestion to fix this. Once that's addressed, the PR should be good to go.

[gemini-code-assist]

It appears there's a typo in the attribute name used to fetch the request timeout. Based on the InferenceEngineConfig dataclass defined in areal/api/cli_args.py, the correct attribute is request_timeout, not rollout_engine_request_timeout. This will cause an AttributeError at runtime.

I've suggested a fix that uses the correct attribute and also renames the local variable for better clarity, as it's passed directly to step_timeout.

Suggested change

	rollout_engine_request_timeout = client.engine.config.rollout_engine_request_timeout
	messages = data["messages"].copy()
	agent = ChatAgent(
	model=AReaLOpenAICompatibleModel(
	openai_client=client, tokenizer=self.tokenizer, model_type="areal"
	openai_client=client, tokenizer=self.tokenizer, model_type="areal",
	model_config_dict=model_config_dict
	),
	token_limit=self.max_total_tokens,
	step_timeout=rollout_engine_request_timeout
	step_timeout = client.engine.config.request_timeout
	messages = data["messages"].copy()
	agent = ChatAgent(
	model=AReaLOpenAICompatibleModel(
	openai_client=client, tokenizer=self.tokenizer, model_type="areal",
	model_config_dict=model_config_dict
	),
	step_timeout=step_timeout

[garrett4wade]

LGTM but the code should be formatted with pre-commit. See CONTRIBUTING.md for instructions.

[garrett4wade]

Please respect gemini's comment as well.

[dsjang2]

Thank you for your feedback.
I will fix the issues and submit PR again.