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README.md

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[![PyPI](https://img.shields.io/badge/pypi-v0.2.0-blue?logo=pypi)](https://pypi.org/project/py-openjudge/)
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[![Documentation](https://img.shields.io/badge/docs-online-blue?logo=readthedocs&logoColor=white)](https://modelscope.github.io/OpenJudge/)
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[📖 Documentation](https://modelscope.github.io/OpenJudge/) | [🤝 Contributing](./docs/community/contributing.md) | [中文](./README_zh.md)
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[📖 Documentation](https://modelscope.github.io/OpenJudge/) | [🤝 Contributing](https://modelscope.github.io/OpenJudge/community/contributing/) | [中文](./README_zh.md)
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</div>
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- 🌐 **Multi-Scenario Coverage:** Extensive support for diverse domains including Agent, text, code, math, and multimodal tasks. 👉 [Explore Supported Scenarios](./docs/built_in_graders/overview.md)
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- 🔄 **Holistic Agent Evaluation:** Beyond final outcomes, we assess the entire lifecycle—including trajectories, Memory, Reflection, and Tool Use. 👉 [Agent Lifecycle Evaluation](./docs/built_in_graders/agent_graders.md)
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- 🌐 **Multi-Scenario Coverage:** Extensive support for diverse domains including Agent, text, code, math, and multimodal tasks. 👉 [Explore Supported Scenarios](https://modelscope.github.io/OpenJudge/built_in_graders/overview/)
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- 🔄 **Holistic Agent Evaluation:** Beyond final outcomes, we assess the entire lifecycle—including trajectories, Memory, Reflection, and Tool Use. 👉 [Agent Lifecycle Evaluation](https://modelscope.github.io/OpenJudge/built_in_graders/agent_graders/)
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-**Quality Assurance:** Every grader comes with benchmark datasets and pytest integration for validation. 👉 [View Benchmark Datasets](https://huggingface.co/datasets/agentscope-ai/OpenJudge)
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### 🛠️ Flexible Grader Building Methods
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Choose the build method that fits your requirements:
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* **Customization:** Easily extend or modify pre-defined graders to fit your specific needs. 👉 [Custom Grader Development Guide](./docs/building_graders/create_custom_graders.md)
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* **Data-Driven Rubrics:** Have a few examples but no clear rules? Use our tools to automatically generate white-box evaluation criteria (Rubrics) based on your data.👉 [Automatic Rubric Generation Tutorial](./docs/building_graders/generate_graders_from_data.md)
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* **Customization:** Easily extend or modify pre-defined graders to fit your specific needs. 👉 [Custom Grader Development Guide](https://modelscope.github.io/OpenJudge/building_graders/create_custom_graders/)
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* **Data-Driven Rubrics:** Have a few examples but no clear rules? Use our tools to automatically generate white-box evaluation criteria (Rubrics) based on your data.👉 [Automatic Rubric Generation Tutorial](https://modelscope.github.io/OpenJudge/building_graders/generate_graders_from_data/)
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* **Training Judge Models ( Coming Soon🚀):** For high-scale and specialized scenarios, we are developing the capability to train dedicated Judge models. Support for SFT, Bradley-Terry models, and Reinforcement Learning workflows is on the way to help you build high-performance, domain-specific graders.
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pip install py-openjudge
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```
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> 💡 More installation methods can be found in the [Quickstart Guide](./docs/get_started/quickstart.md).
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> 💡 More installation methods can be found in the [Quickstart Guide](https://modelscope.github.io/OpenJudge/get_started/quickstart/#installation).
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asyncio.run(main())
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```
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> 📚 Complete Quickstart can be found in the [Quickstart Guide](./docs/get_started/quickstart.md).
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> 📚 Complete Quickstart can be found in the [Quickstart Guide](https://modelscope.github.io/OpenJudge/get_started/quickstart/).
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> **📝 Improving Docs** — Clearer explanations or better examples are always welcome
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> **💡 Proposing Features** — Have ideas for new integrations? Let's discuss!
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📖 See full [Contributing Guidelines](./docs/community/contributing.md) for coding standards and PR process.
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📖 See full [Contributing Guidelines](https://modelscope.github.io/OpenJudge/community/contributing/) for coding standards and PR process.
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We preserved the source code of **v0.1.7 (the latest v0.1.x release)** in the [`v0.1.7-legacy` branch](https://github.com/modelscope/OpenJudge/tree/v0.1.7-legacy).
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- **Migrate to v0.2.0 (recommended)**: follow the **[Installation](#-installation)** section above, then walk through **[Quickstart](#-quickstart)** (or the full [Quickstart Guide](./docs/get_started/quickstart.md)) to update your imports / usage.
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- **Migrate to v0.2.0 (recommended)**: follow the **[Installation](#-installation)** section above, then walk through **[Quickstart](#-quickstart)** (or the full [Quickstart Guide](https://modelscope.github.io/OpenJudge/get_started/quickstart/)) to update your imports / usage.
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If you run into migration issues, please [open an issue](https://github.com/modelscope/OpenJudge/issues) with your minimal repro and current version.
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README_zh.md

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[![PyPI](https://img.shields.io/badge/pypi-v0.2.0-blue?logo=pypi)](https://pypi.org/project/py-openjudge/)
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[![Documentation](https://img.shields.io/badge/docs-online-blue?logo=readthedocs&logoColor=white)](https://modelscope.github.io/OpenJudge/)
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[📖 文档](https://modelscope.github.io/OpenJudge/) | [🤝 贡献指南](./docs/community/contributing.md) | [English](./README.md)
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[📖 文档](https://modelscope.github.io/OpenJudge/) | [🤝 贡献指南](https://modelscope.github.io/OpenJudge/community/contributing/) | [English](./README.md)
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- 🌐 **多场景覆盖:** 广泛支持包括智能体、文本、代码、数学和多模态任务在内的多种领域。→ [探索支持的场景](./docs/built_in_graders/overview.md)
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- 🔄 **全面的智能体评估:** 不仅评估最终结果,我们还评估整个生命周期——包括轨迹、记忆、反思和工具使用。→ [智能体生命周期评估](./docs/built_in_graders/agent_graders.md)
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- 🌐 **多场景覆盖:** 广泛支持包括智能体、文本、代码、数学和多模态任务在内的多种领域。→ [探索支持的场景](https://modelscope.github.io/OpenJudge/built_in_graders/overview/)
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- 🔄 **全面的智能体评估:** 不仅评估最终结果,我们还评估整个生命周期——包括轨迹、记忆、反思和工具使用。→ [智能体生命周期评估](https://modelscope.github.io/OpenJudge/built_in_graders/agent_graders/)
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-**质量保证:** 每个评分器都配有基准数据集和 pytest 集成用于验证。→ [查看基准数据集](https://huggingface.co/datasets/agentscope-ai/OpenJudge)
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### 🛠️ 灵活的评分器构建方法
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选择适合您需求的构建方法:
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* **自定义:** 轻松扩展或修改预定义的评分器以满足您的特定需求。👉 [自定义评分器开发指南](./docs/building_graders/create_custom_graders.md)
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* **数据驱动的评分标准:** 有一些示例但没有明确规则?使用我们的工具根据您的数据自动生成白盒评估标准(Rubrics)。👉 [自动评分标准生成教程](./docs/building_graders/generate_graders_from_data.md)
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* **自定义:** 轻松扩展或修改预定义的评分器以满足您的特定需求。👉 [自定义评分器开发指南](https://modelscope.github.io/OpenJudge/building_graders/create_custom_graders/)
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* **数据驱动的评分标准:** 有一些示例但没有明确规则?使用我们的工具根据您的数据自动生成白盒评估标准(Rubrics)。👉 [自动评分标准生成教程](https://modelscope.github.io/OpenJudge/building_graders/generate_graders_from_data/)
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* **训练评判模型(即将推出🚀):** 对于大规模和专业化场景,我们正在开发训练专用评判模型的能力。SFT、Bradley-Terry 模型和强化学习工作流的支持即将推出,帮助您构建高性能、领域特定的评分器。
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pip install py-openjudge
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> 💡 更多安装方法可在 [快速开始指南](./docs/get_started/quickstart.md) 中找到。
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> 💡 更多安装方法可在 [快速开始指南](https://modelscope.github.io/OpenJudge/get_started/quickstart/) 中找到。
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asyncio.run(main())
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```
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> 📚 完整的快速开始内容可在 [快速开始指南](./docs/get_started/quickstart.md) 中找到。
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> 📚 完整的快速开始内容可在 [快速开始指南](https://modelscope.github.io/OpenJudge/get_started/quickstart/) 中找到。
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> **📝 改进文档** — 更清晰的解释或更好的示例总是受欢迎的
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> **💡 提议新功能** — 有新集成的想法?让我们讨论!
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📖 查看完整的 [贡献指南](./docs/community/contributing.md) 了解编码标准和 PR 流程。
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📖 查看完整的 [贡献指南](https://modelscope.github.io/OpenJudge/community/contributing/) 了解编码标准和 PR 流程。
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我们在 [`v0.1.7-legacy` 分支](https://github.com/modelscope/OpenJudge/tree/v0.1.7-legacy) 中保留了 **v0.1.7(最新的 v0.1.x 版本)** 的源代码。
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- **迁移到 v0.2.0(推荐)**:按照上方的 **[安装](#-安装)** 章节操作,然后浏览 **[快速开始](#-快速开始)**(或完整的 [快速开始指南](./docs/get_started/quickstart.md))来更新您的导入/用法。
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- **迁移到 v0.2.0(推荐)**:按照上方的 **[安装](#-安装)** 章节操作,然后浏览 **[快速开始](#-快速开始)**(或完整的 [快速开始指南](https://modelscope.github.io/OpenJudge/get_started/quickstart/))来更新您的导入/用法。
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如果您遇到迁移问题,请 [提交 issue](https://github.com/modelscope/OpenJudge/issues) 并附上您的最小复现代码和当前版本。
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