Fix in learn to ask

[chenyushuo]

📝 PR Type

• Add new sample
• Update existing sample
• Add new test cases
• Fix test failures
• Documentation/Configuration update

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📚 Description

[Please briefly describe the background, changes, and purpose of this PR. For example:

• Added game_werewolves to demonstrate XYZ functionality in agentscope.
• Fixed test failures in game_test.py caused by agentscope interface changes.
• Updated dependency installation instructions in README.md of agentscope-samples.]

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🧪 Testing Validation

[Please explain how to validate the changes:

1. How to run the added/modified test cases?
2. Is integration testing with agentscope required?
3. Has code been formatted (e.g., pre-commit)?]

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✅ Checklist

Please complete the following checks before submitting the PR:

• All sample code has been formatted with pre-commit run --all-files
• All new/modified test cases have passed (run pytest tests/)
• Test coverage has not decreased (if applicable)
• Sample code follows agentscope best practices (e.g., config management, logging)
• Related documentation in agentscope-samples has been updated (e.g., README.md)

[gemini-code-assist]

Summary of Changes

Hello @chenyushuo, 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 enhances the learn_to_ask example by providing clearer operational details and refining its underlying code. It introduces estimated training costs and token usage in the documentation, offering users better transparency, and simplifies model configuration by removing a redundant parameter.

Highlights

• Documentation Update: The README.md for the learn_to_ask example now includes important details regarding training configuration, estimated token consumption (112 million tokens), and approximate cost ($18) when utilizing Tinker for 4 epochs.
• Code Refinement: The main.py file has been updated to remove the reasoning_parser=None argument from ModelConfig instances, streamlining the model configuration.

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[gemini-code-assist]

Code Review

This pull request updates the 'learn_to_ask' example. The main changes involve removing the reasoning_parser parameter from TunerModelConfig in main.py, likely to align with recent API updates. Additionally, the README.md file has been updated to include estimated token consumption and cost when using the Tinker backend. My review includes a minor suggestion to improve the formatting of the cost information in the README for better clarity.