Fix doc/config issues about prompt/response/sequence lengths

[yanxi-chen]

Description

As the title says.

Checklist

Please check the following items before code is ready to be reviewed.

• Code has passed all tests
• Docstrings have been added/updated in Google Style
• Documentation has been updated
• Code is ready for review

[gemini-code-assist]

Summary of Changes

Hello @yanxi-chen, 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 addresses inconsistencies and potential limitations in the configuration of prompt, response, and sequence lengths across various example configurations and documentation. It primarily updates max_response_tokens and max_model_len values to more appropriate or consistent settings, enhancing the robustness and clarity of the examples for different model training and inference scenarios.

Highlights

• Configuration Updates: Standardized max_response_tokens and max_model_len across numerous example YAML configuration files to ensure consistent and appropriate settings for model operations.
• Documentation Alignment: Updated both English and Chinese tutorial documentation files to reflect the new max_response_tokens and max_model_len parameters, enhancing clarity and accuracy for users.
• Increased Model Lengths: Primarily increased max_model_len from 1280 to 2048 in most example configurations, with specific DPO examples receiving updates to 1536 or 10752 for varied use cases.

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[gemini-code-assist]

Code Review

This pull request consistently updates various documentation and example configuration files to address issues with prompt, response, and sequence lengths. The changes primarily involve increasing max_model_len and adding max_response_tokens and max_model_len where they were missing. This correctly increases the allowable prompt length in many examples, which was previously too restrictive. The changes are logical and improve the usability of the provided examples. I've found one minor issue regarding a potentially misleading configuration in one of the example files, which I've detailed in a specific comment.

[pan-x-c]

/unittest-module-common

[github-actions]

Summary

Tests 📝	Passed ✅	Failed ❌	Skipped ⏭️	Other ❓	Flaky 🍂	Duration ⏱️
34	34	0	0	0	0	4m 56s

Tests

Test Name	Status	Flaky	Duration
tests/common/config_test.py::TestConfig::test_all_examples_are_valid	✅		40.9s
tests/common/config_test.py::TestConfig::test_config_flatten	✅		39ms
tests/common/config_test.py::TestConfig::test_continue_from_checkpoint_is_valid	✅		425ms
tests/common/config_test.py::TestConfig::test_default_workflow	✅		89ms
tests/common/config_test.py::TestConfig::test_load_default_config	✅		3.3s
tests/common/config_test.py::TestConfig::test_max_token_len_per_gpu_set_correctly	✅		93ms
tests/common/config_test.py::TestConfig::test_optimizer_config_propagation	✅		88ms
tests/common/config_test.py::TestConfig::test_update_config_from_ray_cluster	✅		1.9s
tests/common/experience_test.py::TestEID::test_eid_properties	✅		1ms
tests/common/experience_test.py::TestExperience::test_action_mask_and_logprobs_type	✅		1ms
tests/common/experience_test.py::TestExperience::test_assertions	✅		1ms
tests/common/experience_test.py::TestExperience::test_dpo_experience	✅		1ms
tests/common/experience_test.py::TestExperience::test_gather	✅		1ms
tests/common/experience_test.py::TestExperience::test_hf_datasets_conversion	✅		15ms
tests/common/experience_test.py::TestExperience::test_multi_turn_experience	✅		1ms
tests/common/experience_test.py::TestExperience::test_serialize_deserialize	✅		1ms
tests/common/experience_test.py::TestExperience::test_single_turn_experience	✅		1ms
tests/common/experience_test.py::TestExperience::test_to_dict	✅		1ms
tests/common/experience_test.py::TestExperienceConversion::test_batch_conversion	✅		1ms
tests/common/experience_test.py::TestExperienceConversion::test_dpo_experience_batch_conversion	✅		1ms
tests/common/experience_test.py::TestExperienceConversion::test_experience_model_experience_conversion	✅		1ms
tests/common/experience_test.py::TestExperienceConversion::test_gather_experiences_with_custom_fields	✅		1ms
tests/common/experience_test.py::TestExperienceConversion::test_multiturn_experience_batch_converstion	✅		1ms
tests/common/vllm_test.py::ModelWrapperTest_0::test_generate	✅		52.7s
tests/common/vllm_test.py::ModelWrapperTest_1::test_generate	✅		32.6s
tests/common/vllm_test.py::ModelWrapperTest_2::test_generate	✅		42.1s
tests/common/vllm_test.py::TestModelLen_0::test_model_len	✅		17.3s
tests/common/vllm_test.py::TestModelLen_1::test_model_len	✅		16.9s
tests/common/vllm_test.py::TestAPIServer::test_api	✅		22.3s
tests/common/vllm_test.py::TestAsyncAPIServer::test_api_async	✅		22.7s
tests/common/vllm_test.py::TestTokenizer::test_action_mask	✅		244ms
tests/common/vllm_test.py::TestTokenizer::test_action_mask_with_tools	✅		237ms
tests/common/vllm_test.py::TestAPIServerToolCall_0_deepseek_r1::test_api_tool_calls	✅		20.1s
tests/common/vllm_test.py::TestAPIServerToolCall_1::test_api_tool_calls	✅		17.7s

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