feat(training):support online training

[qingTang0305]

Change-Id: Ia388f09600ef9547ab2fe16d595ff01a4ed4dca1

AgentScope-Java Version

[The version of AgentScope-Java you are working on, e.g. 1.0.8, check your pom.xml dependency version or run mvn dependency:tree | grep agentscope-parent:pom(only mac/linux)]

Description

feat(training):#702

Checklist

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

• Code has been formatted with mvn spotless:apply
• All tests are passing (mvn test)
• Javadoc comments are complete and follow project conventions
• Related documentation has been updated (e.g. links, examples, etc.)
• Code is ready for review

[gemini-code-assist]

Summary of Changes

Hello @qingTang0305, 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 introduces a robust online training extension for AgentScope Java, designed to facilitate continuous improvement of agents by integrating with the Trinity-RFT framework. It establishes a data feedback loop from production to training systems, enabling agents to learn and adapt from real-time interactions. The extension provides automated mechanisms for data collection, reward calculation, and training request management, aiming for a minimal setup experience for developers.

Highlights

• New Training Extension Module: A new Maven module, agentscope-extensions-training, has been added to enable online training capabilities for AgentScope Java applications.
• Trinity-RFT Integration: Introduces TrinityClient for seamless interaction with the Trinity-RFT backend, supporting feedback and commit APIs for continuous model optimization.
• Automated Task/Run ID Management: The module provides automated generation and management of Task IDs and Run IDs through TaskIdGenerator, RunRegistry, and RunExecutionContext, simplifying training data tracking.
• Shadow Traffic Training Architecture: A TrainingRouter hook implements a shadow traffic training architecture, allowing a sample portion of production requests to be processed by a 'shadow agent' for training without impacting live service.
• Flexible Training Selection Strategies: Two built-in strategies, SamplingRateStrategy and ExplicitMarkingStrategy, are provided for filtering requests for training, along with an interface for custom selection logic.
• Customizable Reward Calculation: A RewardCalculator interface allows developers to define custom logic for calculating reward values based on shadow agent execution results, crucial for reinforcement learning.
• Comprehensive Documentation: Detailed documentation in both English and Chinese has been added, covering the overview, architecture, core features, quick start guide, and configuration options for the online training extension.

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[gemini-code-assist]

Code Review

This pull request introduces a comprehensive online training extension, which is a significant and well-structured feature. The code is generally of high quality, with good use of reactive programming and clear separation of concerns. I've identified a few areas for improvement, primarily around error handling and documentation consistency, to make the new module more robust and easier to use.

[codecov]

Codecov Report

❌ Patch coverage is 77.03412% with 175 lines in your changes missing coverage. Please review.

Files with missing lines	Patch %	Lines
...gentscope/core/training/runner/TrainingRouter.java	36.80%	77 Missing and 2 partials ⚠️
...o/agentscope/core/training/runner/AgentCloner.java	0.00%	52 Missing ⚠️
...ope/core/training/backend/TrinityModelAdapter.java	71.05%	11 Missing ⚠️
...ope/core/training/strategy/TrainingAnnotation.java	77.77%	0 Missing and 10 partials ⚠️
...gentscope/core/training/runner/TrainingRunner.java	92.55%	6 Missing and 1 partial ⚠️
...cope/core/training/runner/RunExecutionContext.java	92.68%	0 Missing and 3 partials ⚠️
...pe/core/training/runner/TaskExecutionRegistry.java	95.23%	0 Missing and 3 partials ⚠️
...gentscope/core/training/runner/TrainingConfig.java	95.83%	2 Missing and 1 partial ⚠️
...ore/training/strategy/ExplicitMarkingStrategy.java	91.66%	1 Missing and 2 partials ⚠️
...e/training/strategy/TrainingSelectionStrategy.java	0.00%	2 Missing ⚠️
... and 2 more

📢 Thoughts on this report? Let us know!