An open-source post-proxy build layer for reinforcement learning, supervised fine-tuning, and monitoring of proxies.
judgeval is an open-source project aimed at providing a powerful post-construction layer for AI agents. It enhances the post-training process of agents through environmental data and evaluation, supporting both Reinforcement Learning (RL) and Supervised Fine-Tuning (SFT), while also offering real-time monitoring capabilities to ensure the performance and stability of the agents.
This is the machine-readable structured data for this agent. AI systems and search engines use this to understand the agent's capabilities.
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"url": "https://agentsignals.ai/agents/judgeval",
"applicationCategory": "开发工具",
"operatingSystem": "GitHub",
"sameAs": "https://github.com/JudgmentLabs/judgeval",
"installUrl": "https://github.com/JudgmentLabs/judgeval",
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"description": "免费",
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"Provides comprehensive monitoring tools",
"Supported by the open-source community"
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"datePublished": "2025-12-05T17:13:57.723369+00:00",
"dateModified": "2025-12-19T05:09:50.600292+00:00",
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"name": "What is judgeval?",
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"text": "An open-source post-proxy build layer for reinforcement learning, supervised fine-tuning, and monitoring of proxies."
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"name": "What features does judgeval offer?",
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"text": "Supports reinforcement learning and supervised fine-tuning, Provides comprehensive monitoring tools, Supported by the open-source community"
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"name": "What are the use cases for judgeval?",
"acceptedAnswer": {
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"text": "AI agent performance optimization, Agent behavior monitoring, Research and development environment"
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"name": "What are the advantages of judgeval?",
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"text": "开源免费, 强大的训练和监控功能, 社区活跃,支持广泛"
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"@type": "Question",
"name": "What are the limitations of judgeval?",
"acceptedAnswer": {
"@type": "Answer",
"text": "需要一定的技术背景, 文档可能不完整(推测)"
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