Showing 345 open source projects for "testing"

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  • 1
    Java implementation of Sudoku. Visually attractive, interactive version with intelligent and brute force solving strategies.
    Downloads: 0 This Week
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  • 2
    Development of an Inteligent Agent Creation and Testing Framework (IACTF) for use in AI Inteligent Agents scenarios. Also development of a centralized server component for IA management.
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  • 3
    D-Cog (Declarative-Cognition) is a Java based framework for training software components (reusable, object-oriented, interface-driven components). Instead of programmed, software components are trained by example to get the expected results.
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  • 4
    JLife is a Java framework for testing and playing with A-Life. The the main idea is about evolving “creatures”, that consists of chain of commands, that influence both the creature and it's environment.
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  • 5
    The Macro Agent Transport Event-based Simulator (MATES) is intended to efficiently investigate the behavior of distributed agent based systems over mobile ad hoc networks (MANETs). MATES provides an expandable environment for agent-based system testing.
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  • 6
    Evomusic deals with automatic composition of music (midi-files) using evolutionary algorithms. Currently we are testing multiple approaches for doing this successfully, especially neural networks and/or algorithms based on simple music theory.
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  • 7
    Yawn: Yet Another W* Network: a java framework for developing, training and testing neural networks independently of the model and test environment.
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  • 8
    This project aims to produce a structure for the design and implementation of an Artificial Intelligence system based on the idea of determinism. This is to be completed with the creation of an AI system, a testing interface, and example applications.
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  • 9
    SimuBot replaces expensive robot hardware and testing facilities. It allows researchers and enthusiasts alike to explore robotics in 3D with realistic physics. Written in Java, it is platform independent. Any language can be used to program the robots.
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  • 10
    pySPACE

    pySPACE

    Signal Processing and Classification Environment in Python using YAML

    pySPACE is a modular software for processing of large data streams that has been specifically designed to enable distributed execution and empirical evaluation of signal processing chains. Various signal processing algorithms (so called nodes) are available within the software, from finite impulse response filters over data-dependent spatial filters (e.g. CSP, xDAWN) to established classifiers (e.g. SVM, LDA). pySPACE incorporates the concept of node and node chains of the MDP framework. Due...
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  • 11
    OpenAI Realtime Console

    OpenAI Realtime Console

    React app for inspecting, building and debugging with the Realtime API

    openai-realtime-console is a developer tool created by OpenAI that provides a web-based console for experimenting with the Realtime API. The Realtime API enables low-latency, interactive communication with language models, supporting use cases such as live conversations, real-time transcription, and interactive applications. This console serves as a reference implementation, showing how to establish WebRTC or WebSocket connections, send audio or text inputs, and receive model outputs in real...
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  • 12
    lastest

    lastest

    AI-supported visual verification and tests you can actually trust.

    Lastest.cloud is a free, open-source verification of development, self-hosted visual regression and end-to-end testing platform for web applications. An AI agent records you clicking through your running app and generates Playwright tests with multi-selector fallback. Replays are deterministic and token-free, so your CI/CD bill doesn't scale with your test suite. Lastest ships three diff engines side-by-side — pixel (pixelmatch), structural (SSIM), and perceptual (Butteraugli) — so flaky pixel diffs stop crying wolf. ...
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  • 13
    3A-TRE

    3A-TRE

    3A-TRE evaluates traditionally logical expressions under 3 assumptions

    ...The open world assumption (OWA) states that the truth value of a statement that is not included in or inferred from the knowledge explicitly recorded in the system shall be considered unknown. The closed world assumption (CWA) is the assumption that any statement that is not known to be true is false. We distinguish yet another case in software testing. Frequently, there are test stubs which simulate the behaviors of the dependent test modules. In this case, the dependent test modules are always assumed to be true when their results are not available. We call this a stub assumption (SA). 3A-TRE example: echo "CWA: (T and U)" | java -jar PTRE.jar Result: F 3A-PTRE example: (P means possible results) echo "OWA: (T,U and U,F)" | java -jar PTRE.jar Result: U,F
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  • 14
    A scientific framework for testing and learning the learning of a computer.
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  • 15
    The Guiey project is an attempt to develop a system for graphical user interface scripting and testing in Java. Guiey will use a computer by seeing, typing, and clicking - just like a human user.
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  • 16
    Simplepages.ai

    Simplepages.ai

    AI Landing Page Builder that Captures Leads and Takes Payments

    Describe the landing page you need and AI builds a page that captures leads and takes payments. Refine with unlimited AI edits. Live in minutes.
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  • 17

    scripthea

    Scripthea is designed to streamline of crafting prompts for T2I gen.

    Scripthea is a free, open-source Windows application designed to streamline the process of crafting prompts for text-to-image AI generators like Stable Diffusion. Scripthea offers a structured environment for building, testing, and refining prompts, making it an invaluable tool for artists, designers, and AI enthusiasts seeking greater control over their creative outputs. At its core, Scripthea simplifies prompt engineering by breaking down prompts into two components: cues (descriptive text) and modifiers (attributes like style, lighting, or artist references). ...
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  • 18
    Grok-2.5

    Grok-2.5

    Large-scale xAI model for local inference with SGLang, Grok-2.5

    ...Grok-2.5 supports advanced inference with multi-GPU configurations, requiring at least 8 GPUs with more than 40 GB of memory each for optimal performance. It integrates with the SGLang framework to enable serving, testing, and chat-style interactions. The model comes with a post-training architecture and requires the correct chat template to function properly. It is released under the Grok 2 Community License Agreement, encouraging community experimentation and responsible use.
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  • 19
    Ling 3.0 Tiny

    Ling 3.0 Tiny

    Lightweight MoE model for local reasoning, coding, and AI agents

    ...It is specifically optimized for local and resource-constrained deployment and has been validated on NVIDIA DGX Spark, Apple Silicon MacBooks, and Mac mini systems. FP8 testing reached around 100–105 tokens/s on DGX Spark and 86–90 tokens/s on an M4 Pro MacBook. BF16, FP8, and INT4 weights are available, while deployment options include SGLang, vLLM, and experimental Ollama support on Apple Silicon.
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  • 20
    CLIP-ViT-bigG-14-laion2B-39B-b160k

    CLIP-ViT-bigG-14-laion2B-39B-b160k

    CLIP ViT-bigG/14: Zero-shot image-text model trained on LAION-2B

    ...Its training dataset is uncurated and web-sourced, meaning it reflects the biases and risks of large-scale internet data. The model is intended for research use and is not recommended for real-world deployment without domain-specific testing and safety evaluations.
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