Search Results for "test" - Page 6
Sort By:
Showing 629 open source projects for "test"
View related business solutions-
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
-
Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
-
1
bu-agent-sdk
An agent is just a for-loop
...The SDK emphasizes simplicity and control, avoiding heavy orchestration frameworks and instead letting developers specify exactly what tools an agent can employ and how it should signal task completion. This lightweight design means developers can rapidly prototype AI agent behavior, test custom tools, and integrate models like Anthropic’s Claude with minimal overhead. -
2
Manim Skills Repository
Agent skills for Manim to create 3Blue1Brown style animations
...The project aims to wrap common animation logic into structured skills that can be invoked programmatically, reducing boilerplate and allowing creators to focus on creative content rather than low-level animation setup. With clear installation instructions and a collection of test cases, it’s approachable for developers comfortable with Python and interested in educational or technical visualization. -
3
Meta Agents Research Environments (ARE)
Meta Agents Research Environments is a comprehensive platform
...Unlike static benchmarks, ARE supports environments where agents must adapt to changes over time and reason over sequences of actions. It interacts with applications and faces uncertainty. The included Gaia2 benchmark offers 800 scenarios across multiple “universes”. It can test reasoning, memory, tool use, and adaptability. Integration with simulated applications/agent APIs (email, file system, etc.). Support for multiple AI model backends/providers. -
4
Lightweight' GAN
Implementation of 'lightweight' GAN, proposed in ICLR 2021
...Quoting the one-line summary "converge on single gpu with few hours' training, on 1024 resolution sub-hundred images". Augmentation is essential for Lightweight GAN to work effectively in a low data setting. You can test and see how your images will be augmented before they pass into a neural network (if you use augmentation). The general recommendation is to use suitable augs for your data and as many as possible, then after some time of training disable the most destructive (for image) augs. You can turn on automatic mixed precision with one flag --amp. ... -
Try Google Cloud Risk-Free With $300 in CreditUse your credit across every product. Compute, storage, AI, analytics. When it runs out, 20+ products stay free. You only pay when you choose to.
-
5
django-organizations
Multi-user accounts for Django projects
...Users can belong to and own more than one organization (account, group) Invitation and registration functionality works out of the box for many situations and can be extended as needed to fit specific requirements. Start with the base models or use your own for greater customization. Testing each change on all the environments takes some time, you may want to test faster and avoid slowing down development by using pytest against your current environment. -
6
PyTorch Geometric Temporal
Spatiotemporal Signal Processing with Neural Machine Learning Models
The library consists of various dynamic and temporal geometric deep learning, embedding, and Spatio-temporal regression methods from a variety of published research papers. Moreover, it comes with an easy-to-use dataset loader, train-test splitter and temporal snaphot iterator for dynamic and temporal graphs. The framework naturally provides GPU support. It also comes with a number of benchmark datasets from the epidemiological forecasting, sharing economy, energy production and web traffic management domains. Finally, you can also create your own datasets. The package interfaces well with Pytorch Lightning which allows training on CPUs, single and multiple GPUs out-of-the-box. ... -
7
Kiln
Open source platform for managing, testing, and deploying AI apps
Kiln is an open source platform designed to help developers build, evaluate, and deploy AI-powered applications with greater structure and reliability. It provides a unified environment for managing prompts, datasets, and evaluation workflows, allowing teams to iterate on AI behavior in a controlled and measurable way. Kiln emphasizes reproducibility, enabling users to track changes to prompts and models while comparing outputs across different configurations. Kiln also supports systematic... -
8
Humanoid-Gym
Reinforcement Learning for Humanoid Robot with Zero-Shot Sim2Real
...The framework emphasizes the concept of zero-shot sim-to-real transfer, meaning that behaviors learned in simulation can be deployed directly on physical robots with minimal adjustment. To improve reliability and generalization, the framework also includes sim-to-sim validation pipelines that test trained policies across different physics engines. -
9
FireRedASR
Open-source industrial-grade ASR models
FireRedASR is an industrial-grade family of open-source automatic speech recognition models designed to provide high-precision speech-to-text performance across languages including Mandarin, English, and various Chinese dialects, achieving new state-of-the-art benchmarks on public test sets. The project includes multiple model variants to meet different application needs, such as high-accuracy end-to-end interaction using an encoder-adapter-LLM framework and efficient real-time recognition using attention-based encoder-decoder architectures, giving developers flexibility in balancing performance and resource constraints. ... -
Gemini 3 and 200+ AI Models on One PlatformBuild generative AI apps with Vertex AI. Switch between models without switching platforms.
-
10
Nevergrad
A Python toolbox for performing gradient-free optimization
Nevergrad is a Python library for derivative-free optimization, offering robust implementations of many algorithms suited for black-box functions (i.e. functions where gradients are unavailable or unreliable). It targets hyperparameter search, architecture search, control problems, and experimental tuning—domains in which gradient-based methods may fail or be inapplicable. The library provides an easy interface to define an optimization problem (parameter space, loss function, budget) and... -
11
Transformer Debugger
Tool for exploring and debugging transformer model behaviors
Transformer Debugger (TDB) is a research tool developed by OpenAI’s Superalignment team to investigate and interpret the behaviors of small language models. It combines automated interpretability methods with sparse autoencoders, enabling researchers to analyze how specific neurons, attention heads, and latent features contribute to a model’s outputs. TDB allows users to intervene directly in the forward pass of a model and observe how such interventions change predictions, making it... -
12
Covalent workflow
Pythonic tool for running machine-learning/high performance workflows
Covalent is a Pythonic workflow tool for computational scientists, AI/ML software engineers, and anyone who needs to run experiments on limited or expensive computing resources including quantum computers, HPC clusters, GPU arrays, and cloud services. Covalent enables a researcher to run computation tasks on an advanced hardware platform – such as a quantum computer or serverless HPC cluster – using a single line of code. Covalent overcomes computational and operational challenges inherent... -
13
Strawberry GraphQL
A GraphQL library for Python that leverages type annotations
Python GraphQL library based on dataclasses. Strawberry's friendly API allows to create GraphQL API rather quickly, the debug server makes it easy to quickly test and debug. Django and ASGI support allow having your API deployed in production in a matter of minutes. The quick start method provides a server and CLI to get going quickly. Strawberry comes with a mypy plugin that enables statically type-checking your GraphQL schema. A Django view is provided for adding a GraphQL endpoint to your application. ... -
14
DjangoBlog
A blog system based on python3.8 and Django3.0
Articles, pages, categories, tags (add, delete, edit), etc. Articles and pages support Markdown and highlighting. Articles support full-text search. Complete comment feature, include posting reply comment and email notification. Markdown supporting. Sidebar feature, new articles, most readings, tags, etc. OAuth Login supported, including Google, GitHub, Facebook, Weibo, QQ. Memcache supported, with cache auto refresh. Simple SEO Features, notify Google and Baidu when there was a new article... -
15
oscar
Domain-driven eCommerce for Django
Oscar is an open-source eCommerce framework for Django. Oscar makes few assumptions about your project, allowing virtually any part of the framework to be extended and customized. In this way, complex business rules can be captured in an elegant and cohesive way. Any class can be overridden, replaced and extended. This is the key feature that allows any project to be captured accurately in the codebase, no workarounds! A well-designed set of models built on the experience of many e-commerce... -
16
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. -
17
LongBench
LongBench v2 and LongBench (ACL 25'&24')
...It supports bilingual evaluation in English and Chinese to assess multilingual capabilities across extended contexts. Newer versions of the benchmark introduce extremely long context windows ranging from thousands to millions of tokens, enabling researchers to test the limits of modern long-context models. -
18
AICGSecEval
A.S.E (AICGSecEval) is a repository-level AI-generated code security
...AICGSecEval combines static and dynamic evaluation techniques to analyze generated code for vulnerabilities and functional correctness. The framework includes datasets, test cases, and evaluation metrics that measure how AI programming tools perform across multiple programming languages and vulnerability categories. -
19
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... -
20
Multimodal
TorchMultimodal is a PyTorch library
...The design emphasizes composability: you can mix and match encoder, fusion, and decoder components rather than starting from monolithic models. The repository also includes example scripts and datasets for common multimodal tasks (e.g. retrieval, visual question answering, grounding) so you can test and compare models end to end. Installation supports both CPU and CUDA, and the codebase is versioned, tested, and maintained. -
21
MetaCLIP
ICLR2024 Spotlight: curation/training code, metadata, distribution
MetaCLIP is a research codebase that extends the CLIP framework into a meta-learning / continual learning regime, aiming to adapt CLIP-style models to new tasks or domains efficiently. The goal is to preserve CLIP’s strong zero-shot transfer capability while enabling fast adaptation to domain shifts or novel class sets with minimal data and without catastrophic forgetting. The repository provides training logic, adaptation strategies (e.g. prompt tuning, adapter modules), and evaluation... -
22
Sippts
Set of tools to audit SIP based VoIP Systems
Sippts is a set of tools to audit VoIP servers and devices using SIP protocol. Sippts is programmed in Python and it allows us to check the security of a VoIP server using SIP protocol. You can freely use, modify and distribute. If modified, please put a reference to this site. Most security tools can be used for illegal purposes, but the purpose of this tool is to check the security of your own servers and not to use to do bad things. I am not responsible for the misuse of this tool. Sippts... -
23
Cookiecutter Django
Framework for jumpstarting production-ready Django projects quickly
Powered by Cookiecutter, Cookiecutter Django is a framework for jumpstarting production-ready Django projects quickly. Cookiecutter Django works with Python 3.9 and renders Django projects with 100% starting test coverage. It has 12-Factor based settings via django-environment. Secure by default, beacuse we believe in SSL. Optimized development and production settings. Registration is handled via django-allauth. It comes with custom user model ready to go. Provides an optional basic ASGI setup for Websockets and an optional custom static build using Gulp and livereload. ... -
24
Faker for Python
Python package that generates fake data for you
Faker is a Python package that generates fake data for you. Whether you need to bootstrap your database, create good-looking XML documents, fill-in your persistence to stress test it, or anonymize data taken from a production service, Faker is for you. Starting from version 4.0.0, Faker dropped support for Python 2 and from version 5.0.0 only supports Python 3.6 and above. If you still need Python 2 compatibility, please install version 3.0.1 in the meantime, and please consider updating your codebase to support Python 3 so you can enjoy the latest features Faker has to offer. ... -
25
promptmap2
A security scanner for custom LLM applications
...Its scanning workflow uses a dual-LLM architecture in which one model acts as the target being tested and another acts as a controller that evaluates whether an attack succeeded. The repository emphasizes broad coverage, including test rules for prompt stealing, jailbreaks, harmful content generation, hate-related outputs, social bias, and distraction attacks. It also supports multiple providers such as OpenAI, Anthropic, Google, xAI, and open-source models through Ollama, making it flexible for both commercial and local deployments.
