Showing 5 open source projects for "monitor test"

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  • 1
    Evidently

    Evidently

    Evaluate and monitor ML models from validation to production

    Evidently is an open-source Python library for data scientists and ML engineers. It helps evaluate, test, and monitor ML models from validation to production. It works with tabular, text data and embeddings.
    Downloads: 0 This Week
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  • 2
    Opik

    Opik

    Debug, evaluate, and monitor your LLMapps, RAG systems, and agentic AI

    Confidently evaluate, test, and monitor LLM applications. Opik is an open-source platform for evaluating, testing, and monitoring LLM applications. Built by Comet. Record, sort, search, and understand each step your LLM app takes to generate a response. Manually annotate, view, and compare LLM responses in a user-friendly table. Log traces during development and in production.
    Downloads: 0 This Week
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  • 3
    LangWatch

    LangWatch

    The platform for LLM evaluations and AI agent testing

    ...By collecting telemetry data from AI applications, LangWatch allows developers to understand how their systems perform in real-world usage scenarios. The platform includes dashboards that visualize model behavior, enabling teams to monitor trends in response quality and reliability over time. It also provides evaluation tools that allow developers to test prompts and compare outputs across different models or configurations. Through integration with popular AI development frameworks, LangWatch can be embedded directly into AI pipelines to provide continuous monitoring and evaluation.
    Downloads: 0 This Week
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  • 4
    Aden Hive

    Aden Hive

    Outcome driven agent development framework that evolves

    Hive is an open-source agent development framework that helps developers build autonomous, reliable, self-improving AI agents by letting them describe goals in ordinary natural language instead of hand-coding detailed workflows. Rather than manually defining execution graphs, Hive’s coding agent generates the agent graph, connection code, and test cases based on your high-level objectives, enabling outcome-driven agent creation that fits real business processes. Once deployed, agents can capture failure data, evolve automatically to meet their success criteria, and redeploy without constant manual intervention, delivering continual improvement over time. The framework also includes human-in-the-loop nodes, credential management, cost and budget controls, and real-time observability so teams can monitor execution and intervene as needed. ...
    Downloads: 0 This Week
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    Secure File Transfer for Windows with Cerberus by Redwood

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  • 5
    Pezzo

    Pezzo

    Open-source, developer-first LLMOps platform

    Pezzo enables you to build, test, monitor and instantly ship AI all in one platform, while constantly optimizing for cost and performance. Packed with powerful features to streamline your workflow, so you can focus on what matters. Pezzo is a fully cloud-native and open-source LLMOps platform. Seamlessly observe and monitor your AI operations, troubleshoot issues, save up to 90% on costs and latency, collaborate and manage your prompts in one place, and instantly deliver AI changes.
    Downloads: 0 This Week
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