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Back to abacaj/code-eval

Open-source alternatives to Code Eval

5 open-source projects similar to abacaj/code-eval, ranked by how many features they have in common. Compare stars, activity and what each one does to find the best Code Eval alternative.

  • bigcode-project/bigcode-evaluation-harnessAvatar de bigcode-project

    bigcode-project/bigcode-evaluation-harness

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    A framework for the evaluation of autoregressive code generation language models.

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  • confident-ai/deepevalAvatar de confident-ai

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    13,733Ver en GitHub↗

    Deepeval is a framework for testing and evaluating large language model applications. It provides a suite of tools for executing automated regression tests, validating model output quality against defined standards, and tracing the execution of complex agent workflows. By integrating these capabilities into development pipelines, the platform ensures consistent performance and reliability throughout the software lifecycle. The platform distinguishes itself through its focus on programmatic validation and observability. It utilizes secondary language models to score output quality and employs

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  • explodinggradients/ragasAvatar de explodinggradients

    explodinggradients/ragas

    14,400Ver en GitHub↗

    Ragas is an evaluation framework and performance benchmark designed to quantify the quality of retrieval augmented generation pipelines. It functions as an application optimizer to identify bottlenecks in language model workflows using automated metrics and model-based scoring. The framework includes a system for generating synthetic datasets that mimic production scenarios and edge cases to create realistic test cases. It enables reference-free assessment, allowing the evaluation of response quality by analyzing grounding in the provided context without requiring gold-standard labels. The s

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  • uptrain-ai/uptrainAvatar de uptrain-ai

    uptrain-ai/uptrain

    2,352Ver en GitHub↗

    UpTrain is an open-source unified platform to evaluate and improve Generative AI applications. We provide grades for 20+ preconfigured checks (covering language, code, embedding use-cases), perform root cause analysis on failure cases and give insights on how to resolve them.

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