Search Results for "unitils-test"
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Showing 42 open source projects for "unitils-test"
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Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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Superpowers
An agentic skills framework & software development methodology
Superpowers Framework is a widely-used agentic skills framework and methodology for software development that equips coding agents like Claude Code with structured capabilities to plan, develop, test, and review code systematically. Instead of simply generating code, Superpowers drives an AI through a thoughtful software engineering workflow that starts with clarifying project intent, teasing out a detailed specification, and creating an implementation plan that is readable and actionable. It incorporates test-driven development, task planning, and sub-agent orchestration so that each engineering task is executed, checked, and iterated upon with rigor rather than ad-hoc improvisation. ... -
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Goose
AI coding agent that's more than suggestions - install, execute, edit+
Goose is an open-source, extensible AI agent that enhances the software development process by going beyond traditional code suggestions. It allows developers to install, execute, edit, and test code with any large language model (LLM), facilitating a more efficient and streamlined workflow. Designed to operate locally within a developer's environment, Goose integrates seamlessly with various tools and platforms, providing a customizable and powerful assistant for coding tasks. Its architecture supports extensibility, enabling users to tailor the agent to their specific needs and preferences. ... -
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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). -
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OpenClaw Installer
ClawdBot one-click deployment tool
...It supports multiple platforms, including macOS, Linux distributions (Ubuntu, Debian, CentOS), and Windows environments via compatible shells, and simplifies otherwise complex installation steps into a guided, terminal-based experience. The tool also includes options to test API connections, validate channel integrations like Telegram or Discord bots, and launch persistent services that keep OpenClaw running in the background. -
Error to trace to log to deploy. One click. No SSH.AppSignal links every error to the trace, the trace to the log, the log to the deploy that shipped it.
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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. ... -
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Kheish
Kheish: A multi-role LLM agent for tasks like code auditing
Kheish is a framework designed for cybersecurity professionals to automate penetration testing tasks, providing tools to streamline security assessments. -
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AgentOps
Python SDK for agent monitoring, LLM cost tracking, benchmarking, etc.
Industry-leading developer platform to test and debug AI agents. We built the tools so you don't have to. Visually track events such as LLM calls, tools, and multi-agent interactions. Rewind and replay agent runs with point-in-time precision. Keep a full data trail of logs, errors, and prompt injection attacks from prototype to production. Native integrations with the top agent frameworks. -
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Coze Loop
Next-generation AI Agent Optimization Platform
...The project aims to simplify the increasingly complex workflow of building reliable AI agents by offering integrated tools for debugging, evaluation, observability, and optimization. Through its visual playground, developers can test prompts interactively and compare outputs across different language models. The platform also includes automated evaluation capabilities that assess agent performance across multiple quality dimensions such as accuracy and compliance. Its observability layer captures detailed execution traces, enabling teams to understand how inputs, prompts, and tools interact during runtime. ... -
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GitHub Agentic Workflows
GitHub Agentic Workflows
GitHub Agentic Workflows is an experimental CLI extension and framework for the gh GitHub CLI that lets developers author automation driven by natural language specifications instead of hand-written code, compiling those descriptions into GitHub Actions workflows that run AI agents (like Copilot, Claude Code, or Codex) on schedule or in response to repository events. By writing intent in markdown files, a developer can quickly generate .yml Actions workflows that perform tasks such as... -
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.
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Flint Chart
Visualization language that lets AI agents create expressive charts
...One Flint input can compile into native Vega-Lite, ECharts, or Chart.js specifications. The repository includes a TypeScript library, an MCP server, a demo site, documentation, test data, and an early Python port. It is especially useful for AI agents that need to create reliable visualizations from structured data during analysis or reporting workflows. -
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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. -
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Skills For Real Engineers
Skills for Real Engineers. Straight from my .claude directory
Skills For Real Engineers is a curated collection of modular AI “skills” designed to improve how developers interact with coding agents by enforcing structured engineering workflows. Each skill is a small, focused instruction set that guides an AI through tasks such as planning, refactoring, testing, or architectural analysis. Instead of relying on vague prompts, the system encodes repeatable processes that ensure consistent and higher-quality outputs. The repository includes tools for... -
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AIPex
AI browser automation assistant, no migration and privacy first
AIPex is an AI-augmented development toolkit and workflow platform that aims to accelerate software productivity by integrating intelligent assistants, code generation tools, and customizable automation patterns directly into developer workflows. Rather than treating AI as a separate helper, AIPex embeds AI capabilities into common tasks like scaffolding components, generating tests, analyzing code quality, and performing refactors, allowing developers to stay in flow while benefiting from... -
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Microsoft Agent Skills
Skills, MCP servers, Custom Agents, Agents.md for SDKs
Microsoft Agent Skills is an actively maintained repository of skills, custom agents, templates, and MCP configuration files designed to extend AI coding assistants with deep knowledge about Azure SDKs and Microsoft AI Foundry services. The project bundles over a hundred domain-specific skills that teach AI agents how to perform tasks like Azure resource provisioning, SDK usage patterns, infrastructure setup, and common DevOps workflows, bridging the gap between agent reasoning and... -
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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. ... -
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Arcade AI
Arcade Tool Development Kit (TDK), Worker, Evals, and CLI
...This repository contains the core Arcade libraries, organized as separate packages for maximum flexibility and modularity. Evaluation framework for testing tool performance. Test your MCP server's tools, resources, prompts, elicitation, and OAuth 2. MCPJam is compliant with the latest MCP specs. Connect to any MCP server. MCPJam inspector supports STDIO, SSE, and Streamable HTTP transports. -
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LiteMultiAgent
The Library for LLM-based multi-agent applications
LiteMultiAgent is a lightweight and extensible multi-agent reinforcement learning (MARL) platform designed for rapid experimentation. It allows researchers to design and test coordination, competition, and collaboration scenarios in simulated environments. -
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Agentex
Open source codebase for Scale Agentex
AgentEX is an open framework from Scale for building, running, and evaluating agentic workflows, with an emphasis on reproducibility and measurable outcomes rather than ad-hoc demos. It treats an “agent” as a composition of a policy (the LLM), tools, memory, and an execution runtime so you can test the whole loop, not just prompting. The repo focuses on structured experiments: standardized tasks, canonical tool interfaces, and logs that make it possible to compare models, prompts, and tool sets fairly. It also includes evaluation harnesses that capture success criteria and partial credit, plus traces you can inspect to understand where reasoning or tool use failed. ... -
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Inspect Petri
An alignment auditing agent capable of exploring alignment hypothesis
Inspect Petri is an open-source alignment auditing agent that lets researchers rapidly test concrete safety hypotheses against target models using realistic, multi-turn scenarios. Instead of building bespoke evals, Inspect Petri automatically generates audit environments from seed “special instructions,” orchestrates an auditor model to probe a target model, and simulates tool use and rollbacks to surface risky behaviors. -
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Alan AI
In-App assistant SDK to build a multimodal conversational UX websites
...Alan is a conversational voice AI platform that lets you create an intelligent voice assistant for your app. It offers all the necessary tools to design, embed, and host your voice solutions. A powerful web-based IDE where you can write, test and debug dialog scenarios for your voice assistant or chatbot. Alan's AI-backend powered by the industry’s best Automatic Speech Recognition (ASR), Natural Language Understanding (NLU) and Speech Synthesis. The Alan Cloud provisions and handles the infrastructure required to maintain your voice deployments and perform all the voice processing tasks. ... -
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improve
Use your most capable model to audit your codebase
...It can run full, quick, deep, security-focused, branch-scoped, and feature-suggestion audits. It maps repository conventions, identifies findings, writes ordered markdown plans, and records verification steps such as lint, build, and test commands. It is useful for teams that want AI-assisted technical planning without letting the planning model directly change production code. -
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LabClaw
Operating Layer for LabOS (Stanford-Princeton AI Co-Scientists)
LabClaw is an open-source AI experimentation and agent orchestration platform designed to help developers build, test, and iterate on complex autonomous workflows in a controlled and modular environment. It provides a framework for composing multiple tools, prompts, and execution steps into structured pipelines that can be reused and evaluated across different scenarios. The system emphasizes experimentation, allowing users to run multiple variations of agent workflows, compare outputs, and refine performance over time. ... -
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Ralph
Autonomous AI agent loop that runs until all PRD items are complete
Ralph is an autonomous AI coding loop that repeatedly runs agentic development tools until every item in a product requirements document is complete. It is designed to work with Amp or Claude Code, launching a fresh AI instance on each iteration to avoid context overload. Instead of relying on one long conversation, Ralph keeps progress through git history, a structured prd.json file, and an append-only progress.txt memory file. Each run selects the highest-priority unfinished user story,... -
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AutoAgent AI
Autonomous harness engineering
AutoAgent is an experimental AI framework focused on autonomous agent engineering, where a meta-agent iteratively improves another agent’s architecture without direct human intervention. Instead of manually tuning prompts or workflows, developers define high-level goals in a configuration file, and the system continuously modifies its own tools, orchestration, and logic based on benchmark performance. It operates through a loop of testing, analyzing failures, and refining the agent’s... -
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Sandbox Agent
Run Coding Agents in Sandboxes
Sandbox Agent by Rivet is an experimental framework for running AI agents in controlled, isolated environments where they can safely execute code, interact with tools, and perform autonomous tasks without risking system integrity. It is designed to provide a secure sandbox that allows agents to test actions, manipulate files, and run commands while enforcing strict boundaries and monitoring capabilities. The project focuses on enabling more reliable and auditable agent behavior by separating execution from the host environment, which is especially important for applications involving automation, code generation, or system-level operations. ...