Scale computer-use 2.0 with open-source drivers, cross-OS sandboxes, and benchmarks for training, evaluation, and data generation.
- apple
- cua
- lume
- macos
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BISHENG is an open LLM devops platform for next generation Enterprise AI applications. Powerful and comprehensive features include: GenAI workflow, RAG, Agent, Unified model management, Evaluation, SFT, Dataset Management, Enterprise-level System Management, Observability and more.
TranslatedOpen-source AI API relay benchmark, rankings & switcher for Claude Code / Codex: measured availability, latency and price
A Go framework for building production agent systems with graph workflows, tools, memory, A2A, AG-UI, MCP, evaluation, and observability.
WFGY is heading toward WFGY 5.0 Polaris Protocol, a major open-source release for AI reasoning, RAG, agents, and real-world workflows. Includes Problem Map, Global Debug Card, WFGY 4.0, and the CFV Easter Egg.
MCP gateway & OAuth MCP servers. LangGraph agent: memory, eval/tracking, PII guard, context trimming. Docker quick start for enterprise agents.
- agentic-ai
- ai-agents
- context-engineering
- enterprise-ai
TranslatedHelixHarness provides complete foundational capabilities for AI Coding engineering, and also supports different enterprises and teams in combining their own business knowledge, engineering standards, and R&D processes to continuously build and evolve their own dedicated Harness
- agent-harnesses
- ai-coding
- ai-coding-agent
- coding-agent
Feather agent harness, training integrations, and evaluation tools for knowledge work
Multi-agent research execution system: paper reproduction, benchmark evaluation, AutoResearch and claim-evidence graphs
- auto-research
- golang
- multi-agent
- paper-reproduction
LLM and agent evaluation for Java & Kotlin. Runs in JUnit and CI. Spring AI, LangChain4j, Koog, Embabel, and any LLM client.
- agent-evaluation
- evaluation-framework
- evaluation-metrics
- java
Open-source simulation harness for testing AI agents. Simulate LLM and tool calls to test edge cases, failure paths, and agent logic without live API calls.
- ai-agents
- ai-testing
- llm
- llm-evaluation
Framework-agnostic evaluation harness for Go — test your MCP servers and AI agents with scored, CI-ready checks.