Showing 146 open source projects for "unitils-test"

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  • 1
    TTRL

    TTRL

    Test-Time Reinforcement Learning

    TTRL is an open-source framework for test-time reinforcement learning in large language models, with a particular focus on reasoning tasks where ground-truth labels are not available during inference. The project addresses the problem of how to generate useful reward signals from unlabeled test-time data, and its central insight is that common test-time scaling practices such as majority voting can be repurposed into reward estimates for online reinforcement learning. ...
    Downloads: 0 This Week
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  • 2
    Ragas

    Ragas

    Supercharge Your LLM Application Evaluations

    Objective metrics, intelligent test generation, and data-driven insights for LLM apps. Ragas is your ultimate toolkit for evaluating and optimizing Large Language Model (LLM) applications. Say goodbye to time-consuming, subjective assessments and hello to data-driven, efficient evaluation workflows. Don't have a test dataset ready? We also do production-aligned test set generation.
    Downloads: 0 This Week
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  • 3
    Qodo Cover

    Qodo Cover

    AI tool that generates tests to improve code coverage quickly

    ...It supports scanning entire repositories to automatically detect test files, gather relevant context, and extend test suites accordingly.
    Downloads: 0 This Week
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  • 4
    CodiumAI Cover-Agent

    CodiumAI Cover-Agent

    CodiumAI Cover-Agent: An AI-Powered Tool for Automated Test Generation

    CodiumAI Cover Agent aims to help efficiently increasing code coverage, by automatically generating qualified tests to enhance existing test suites.
    Downloads: 0 This Week
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  • 5
    Deepchecks

    Deepchecks

    Test Suites for validating ML models & data

    Deepchecks is the leading tool for testing and for validating your machine learning models and data, and it enables doing so with minimal effort. Deepchecks accompany you through various validation and testing needs such as verifying your data’s integrity, inspecting its distributions, validating data splits, evaluating your model and comparing between different models. While you’re in the research phase, and want to validate your data, find potential methodological problems, and/or validate...
    Downloads: 13 This Week
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  • 6
    PML

    PML

    The easiest way to use deep metric learning in your application

    This library contains 9 modules, each of which can be used independently within your existing codebase, or combined together for a complete train/test workflow. To compute the loss in your training loop, pass in the embeddings computed by your model, and the corresponding labels. The embeddings should have size (N, embedding_size), and the labels should have size (N), where N is the batch size. The TripletMarginLoss computes all possible triplets within the batch, based on the labels you pass into it. ...
    Downloads: 1 This Week
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  • 7
    Giskard

    Giskard

    Collaborative & Open-Source Quality Assurance for all AI models

    ...Giskard automatically generates relevant tests based on the vulnerabilities detected by the scan. You can easily customize the tests depending on your use case by defining domain-specific data slicers and transformers as fixtures of your test suites.
    Downloads: 0 This Week
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  • 8
    amrlib

    amrlib

    A python library that makes AMR parsing, generation and visualization

    ...A QT-based GUI to facilitate the conversion of sentences to graphs and back to sentences. Methods to plot AMR graphs in both the GUI and as library functions. Training and test code for both the StoG and GtoS models. A SpaCy extension that allows direct conversion of SpaCy Docs and Spans to AMR graphs. Sentence to Graph alignment routines FAA_Aligner (Fast_Align Algorithm), based on the ISI aligner code detailed in this paper. RBW_Aligner (Rule Based Word) for a simple, single token to single node alignment.
    Downloads: 4 This Week
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  • 9
    FuzzyAI Fuzzer

    FuzzyAI Fuzzer

    A powerful tool for automated LLM fuzzing

    ...The framework can be integrated into development pipelines to continuously test AI APIs and detect weaknesses before deployment. FuzzyAI provides testing tools, datasets, and evaluation workflows that help researchers measure how well models resist harmful instructions or attempts to bypass safety mechanisms.
    Downloads: 2 This Week
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  • 10
    FullTClash

    FullTClash

    General proxy performance testing tool based on Clash using Telegram

    ...The front end part uses Telegram API as the interactive interface, which needs to be used in conjunction with Telegram, that is, a Telegram robot (bot), FullTClash bot is a Telegram robot (hereinafter referred to as bot) carrying its test tasks.
    Downloads: 0 This Week
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  • 11
    Rogue

    Rogue

    AI Agent Evaluator & Red Team Platform

    Rogue is an open-source evaluation and red-team framework designed to test the reliability, safety, and policy compliance of AI agents. The platform automatically interacts with an AI agent by generating dynamic scenarios and multi-turn conversations that simulate real-world interactions. Instead of relying solely on static test scripts, Rogue uses an agent-as-a-judge architecture where one agent probes another agent to detect failures or unexpected behaviors.
    Downloads: 2 This Week
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  • 12
    Freqtrade

    Freqtrade

    Free, open source crypto trading bot

    Freqtrade is a free and open-source crypto trading bot written in Python. It is designed to support all major exchanges and be controlled via Telegram or WebUI. It contains backtesting, plotting, and money management tools as well as strategy optimization by machine learning. Always start by running a trading bot in Dry-run and do not engage money before you understand how it works and what profit/loss you should expect. We strongly recommend you have basic coding skills and Python...
    Downloads: 4 This Week
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  • 13
    PaddleX

    PaddleX

    PaddlePaddle End-to-End Development Toolkit

    ...Users only need to put pictures belonging to the same category in the same folder. When the model is trained, we need to divide the training set, the validation set and the test set. Therefore, we need to divide the above data. Using the paddlex command, the data set can be randomly divided into 70% training set, 20% validation set and 10% test set. If you use the PaddleX visualization client for model training, the data set division function is integrated in the client, and you do not need to use command division by yourself.
    Downloads: 1 This Week
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  • 14
    skfolio

    skfolio

    Python library for portfolio optimization built on top of scikit-learn

    ...It supports a wide range of allocation methods, from classical mean-variance optimization to modern techniques that rely on clustering, factor models, and risk-based allocations. The framework also includes tools for evaluating portfolio performance under different market conditions, enabling users to test robustness and reduce the risk of overfitting.
    Downloads: 14 This Week
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  • 15
    Dagger

    Dagger

    Containerized automation engine for programmable CI/CD workflows

    Dagger is an open source automation engine designed to build, test, and deliver software in a consistent and programmable way. It enables developers to define software delivery workflows using code instead of complex shell scripts or configuration files. Dagger executes tasks inside containers, ensuring that automation runs in identical environments across local machines, CI servers, or cloud infrastructure.
    Downloads: 16 This Week
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  • 16
    Reef

    Reef

    Continual learning infra for self-improving agents

    ...Weight-training workflows can integrate with systems such as Slime and SGLang, while harness optimization can run without local training GPUs. Versioned artifacts let deployments stay operational while new candidates are evaluated and released. Reef also supports test-time learning scenarios where measurable task outcomes can drive iterative improvement.
    Downloads: 0 This Week
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  • 17
    ASSERT

    ASSERT

    Requirement-driven evaluation harness for AI agents and LLM

    ...It turns natural-language specifications, policies, product requirements, and launch criteria into structured tests that can be reviewed, executed, scored, and improved. The pipeline derives behavior categories, generates single-turn and multi-turn test cases, runs them against a target system, and uses an LLM judge to score conversations against the stated policies. It can evaluate hosted models, custom agents, multi-agent systems, REST clients, and frameworks such as LangGraph, CrewAI, AutoGen, DSPy, LlamaIndex, and OpenAI Agents SDK. ASSERT is designed to close the gap between what a system is supposed to do and what evaluation actually measures. ...
    Downloads: 0 This Week
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  • 18
    PySpur

    PySpur

    Visual tool for building, testing, and deploying AI agent workflows

    PySpur is a visual development environment designed to help AI engineers build, test, and iterate on agent-based workflows more efficiently. It provides a structured playground where users can define test cases, construct agents either through Python code or a graphical interface, and continuously refine their behavior. It addresses common challenges in AI agent development such as prompt tuning difficulties and lack of visibility into workflow execution.
    Downloads: 0 This Week
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  • 19
    SWE-agent

    SWE-agent

    SWE-agent takes a GitHub issue and tries to automatically fix it

    ...GPT-4) into software engineering agents that can resolve issues in real GitHub repositories. On the SWE-bench, the SWE-agent resolves 12.47% of issues, achieving state-of-the-art performance on the full test set. We accomplish our results by designing simple LM-centric commands and feedback formats to make it easier for the LM to browse the repository, and view, edit, and execute code files. We call this an Agent-Computer Interface (ACI).
    Downloads: 0 This Week
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  • 20
    TurboQuant+

    TurboQuant+

    Implementation of TurboQuant (ICLR 2026)

    ...It is designed to be used in conjunction with modern machine learning workflows, particularly those involving large models that require optimization for deployment. TurboQuant Plus focuses on experimentation and performance tuning, allowing developers to test different configurations and evaluate trade-offs. Its architecture supports extensibility, enabling further development of quantization methods and integration with existing ML pipelines.
    Downloads: 6 This Week
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  • 21
    tf2onnx

    tf2onnx

    Convert TensorFlow, Keras, Tensorflow.js and Tflite models to ONNX

    ...TensorFlow has many more ops than ONNX and occasionally mapping a model to ONNX creates issues. tf2onnx will use the ONNX version installed on your system and installs the latest ONNX version if none is found. We support and test ONNX opset-13 to opset-17. opset-6 to opset-12 should work but we don't test them. If you want the graph to be generated with a specific opset, use --opset in the command line, for example --opset 13. When running under tf-2.x tf2onnx will use the tensorflow V2 controlflow.
    Downloads: 0 This Week
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  • 22
    npcpy

    npcpy

    The AI toolkit for the AI developer

    npcpy is a Python-based agent framework and command-line toolkit (the NPC Shell) for developers to build, test, and integrate AI agents into their workflows, including both command-line and GUI interfaces via NPC Studio. Welcome to npcpy, the core library of the NPC Toolkit that supercharges natural language processing pipelines and agent tooling. npcpy is a flexible framework for building state-of-the-art applications and conducting novel research with LLMs.
    Downloads: 5 This Week
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  • 23
    Cangjie Skill

    Cangjie Skill

    Distill high-value content like books, long videos, podcasts, and more

    ...Strict verification rejects generic or weak ideas that lack independent evidence, predictive value, or meaningful uniqueness. The generated package can include an overview, glossary, reference graph, long-form digest, individual skill files, and test prompts. Completed skills can be installed for compatible coding agents such as Claude Code and Cursor.
    Downloads: 6 This Week
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  • 24
    Agentless

    Agentless

    An agentless approach to automatically solve software development

    Agentless is an open-source framework that applies large language models to automatically resolve software development issues without relying on complex autonomous agent systems. The project proposes an alternative approach to AI-driven code repair that avoids the overhead of multi-agent orchestration by using a structured pipeline for identifying and fixing bugs. When solving a problem, the system first performs localization to determine which files, functions, or code segments are most...
    Downloads: 6 This Week
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  • 25
    GPT-API-free

    GPT-API-free

    Free ChatGPT&DeepSeek API Key

    ...It offers a proxy-based approach that allows developers to interact with language models through a simplified interface, often requiring minimal configuration. The system is designed to lower barriers for developers who want to test or build applications using conversational AI without managing billing or complex authentication flows. It supports common API formats similar to widely used AI services, making it easier to integrate into existing projects. The project is particularly useful for rapid prototyping, educational purposes, and lightweight applications. ...
    Downloads: 4 This Week
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