155 个 · 框架 · AI 核心
Dust：一款受 React/Vue 启发的现代化、组件化 Dart Web 框架，基于 WebAssembly（WASM）构建，具有高性能与流畅的开发体验，可使用 Dart 构建健壮、类型安全的 Web 应用。Dust: A modern, component-based Dart web framework inspired by React/Vue. Built with WebAssembly (WASM) for high performance and a seamless developer experience. Create robust, type-safe web applications with the power of Dart.
用于评估检索增强视觉语言模型在循证医学视觉问答中表现的研究框架Research framework evaluating retrieval-augmented vision-language models for evidence-grounded medical visual question answering.
GitHub 上最新 Agent 框架的实时索引，按发布时间而非 star 数排序。Live index of the newest agent frameworks shipping on GitHub, sorted by recency not stars
面向 Bun 的、强约定的全栈框架，主要用户是 AI Agent。八个原语，统一的 authz 系统覆盖所有入口，错误信息附带可直接执行的修复命令。可在 PaaS 上免费起步，扩容无需改动应用代码。Bun-only, opinionated full-stack framework where the primary user is an AI agent. Eight primitives, one authz system across every surface, errors that carry an exact fix command. Start free on a PaaS; scale out without changing app code.
面向银行内部产品审计的深度研究 LLM Agent + RAG 平台，提供带引用报告、PDF 导出与 pgvector 支持。Deep-research LLM agent + RAG platform for internal bank-product audit — cited reports, PDF export, pgvector
BMAD 的精简版本，对较小 AI 计划额度更友好。A slimmed-down version of BMAD made to be friendlier to smaller AI plan limits
AI Agent 集群的开源任务控制中心 —— 对话即可配置，Agent 负责执行，人类负责审批。Open-source mission control for AI agent fleets — chat to provision, agents to operate, humans to approve.
用于实时技术分析与市场执行的自主 agentic 框架。Autonomous agentic framework for real-time technical analysis and market execution.
1,716 道 AI/ML 面试题（含答题框架）、69 张架构图、按角色的学习路径，以及语音驱动的模拟面试工具。覆盖 LLM、RAG、agent、MCP/A2A、系统设计、MLOps、安全与云部署。1,716 AI/ML interview questions with answer frameworks, 69 architecture diagrams, role-based study paths, and a voice-enabled mock interview simulator. Covers LLMs, RAG, agents, MCP/A2A, system design, MLOps, safety and cloud deployment.
🤖 生产级 AI agent 编排平台，支持实时流式输出与多工具执行🤖 Orchestrate AI agents with ease using this production-ready platform, featuring real-time streaming and multi-tool execution capabilities.
基于 RAG、LangGraph 多 agent workflow、FastAPI 与 PostgreSQL（pgvector）构建的 AI 教育内容生成平台。生产级架构，集成 LangSmith tracing。AI-powered educational content generation platform using RAG, LangGraph multi-agent workflows, FastAPI, and PostgreSQL with pgvector. Production-ready architecture with LangSmith tracing.
自托管、100% 本地的 AI 平台——在一个 Docker 栈中集成 LLM 推理、RAG 与知识图谱。无需 API key。Self-hosted, 100% local AI platform — LLM inference, RAG, and knowledge graphs in one Docker stack. No API keys.
一切留痕：需求即 issue，决策即审批评论，工作即 PR，理由即该 PR 的记录。协调器将对话中继到 GitHub，并为每个角色派生沙盒化会话，各自仅持有自己的规则集。Everything on the record: a requirement is an issue, a decision is an approval comment, work is a PR, rationale is that PR's record. The orchestrator relays conversation to GitHub and spawns sandboxed role sessions, each with only its own rulebook.
🧠 构建模拟人类记忆的 AI 认知架构，分离情景记忆与语义记忆，并保证多语言支持与数据完整性🧠 Build a cognitive architecture for AI that mimics human memory, separating episodic and semantic memory while ensuring multilingual support and data integrity.
基于 Microsoft Agent Framework (.NET) 的 LLM Agent 三层评估：运行时护栏、PR 闸口、校准过的评审者。该框架可自我评估。Three-tier evaluation for LLM agents on Microsoft Agent Framework (.NET): runtime guardrails, a PR gate, and calibrated judges. The framework evaluates itself.
2026 年顶级开源 AI Agent 🤖 | 最佳自主工具与框架Top Open-Source AI Agents 2026 🤖 | Best Autonomous Tools & Frameworks
面向产品和 AI Agent 的自托管时序记忆平台。Self-hosted temporal memory platform for products and AI agents.
🛠️ 使用 Haystack 轻松构建强大搜索系统，该框架用于开发端到端问答与搜索应用。🛠️ Build powerful search systems effortlessly with Haystack, a framework for developing end-to-end question answering and search applications.
通过一次 wrap() 调用为 LLM 流水线构建运行时可靠性守卫，可配置地防御常见生产故障Build runtime reliability guards for LLM pipelines with one wrap() call and configurable protection against common production failures
Orchestra 的 AI 服务器——蓝图生成、任务分配、Clover 助手与知识图谱AI server for Orchestra- blueprint generation, task assignment, Clover assistant, and knowledge graph
WordPress 共享 AI 基础设施：provider 凭证、实时模型、提示词、标准化请求及 AI-Scribe 和兼容插件的使用记录。Shared AI infrastructure for WordPress: provider credentials, live models, prompts, normalised requests and usage records for AI-Scribe and compatible plugins.
基于环境凭证的 CrewAI scaffold 与 Streamlit kickoff-client 学习。CrewAI scaffold and Streamlit kickoff-client study with environment-only credentials.
基于架构决策记录（ADR）理念的 Memory Framework，用于 AI agent（Claude Code、Codex、Antigravity……）之间的知识共享。支持 agent 安装，vector（Postgres + pgvector）+ graph（Neo4j）双骨干，通过本地 gateway 管理，支持多种本地 LLM 后端，具备完整 provenance、合并、遥测等能力。Memory Framework based on the idea of Architectural Decision Records, shared knowledge between AI agents (Claude Code, Codex, Antigravity ...). Agent installable, vector (Postgres + pgvector) + graph (Neo4j) backbone, managed through a local gateway, supporting multiple local LLM backends, with full provenance, consolidation, telemetry and more
Mistral Studio 产品营销策略、品类叙事、定位与信息框架、从专业消费者到企业的分层、销售作战卡、品牌资产与市场分析。Mistral Studio Product Marketing Strategy, Category Narrative, Positioning & Messaging Framework, Prosumer-to-Enterprise Segmentation, Sales Battlecards, Brand Assets & Market Analysis.
企业级数字支付平台：Java 21 / Spring Boot 3 微服务、Kafka 事件驱动、六边形（端口与适配器）架构，由专业 AI Agent 团队以 spec 驱动并编排，包含完整 CI/CD、GitOps 和供应链安全。Enterprise-grade digital payment platform: Java 21 / Spring Boot 3 microservices, Kafka event-driven, hexagonal (ports & adapters) architecture, spec-driven and orchestrated by a team of specialized AI agents. Includes full CI/CD, GitOps, and supply-chain security.
构建安全、有治理、可观测、成本可控的云与 AI 平台能力的实用参考框架。A practical reference framework for building secure, governed, observable, and cost-aware Cloud & AI platform capabilities.
企业知识智能平台：基于权限感知的搜索、助手与 agent，覆盖公司现有工具栈。Enterprise knowledge intelligence platform. Permission aware search, assistant and agents over the tools a company already runs.
受治理的、与 provider 无关的运行时，面向证据驱动的自主软件工程、研究和数据分析工作流。Governed, provider-neutral runtime for evidence-driven autonomous software engineering, research, and data-analysis workflows.
AI 驱动的 DevSecOps 可观测平台，基于 Gemini 2.5、LangChain 与 RAG 驱动的 runbook 监控基础设施、检测威胁并自动响应。AI-powered DevSecOps observability platform; monitors infrastructure, detects threats, and responds using Gemini 2.5, LangChain, and RAG-powered runbooks.
端到端 Python RAG 框架，包含文档摄取、语义搜索、对话式 AI、多用户检索、可观测性、结构化输出与评估。An end-to-end Python RAG framework featuring document ingestion, semantic search, conversational AI, multi-user retrieval, observability, structured outputs, and evaluation.
AI Kubernetes 升级智能平台——通过确定性兼容性分析 + RAG-grounded LLM 规划，实现安全集群升级（EKS/GKE/AKS/OpenShift/kubeadm）。AI Kubernetes Upgrade Intelligence Platform — deterministic compatibility analysis + RAG-grounded LLM planning for safe cluster upgrades (EKS/GKE/AKS/OpenShift/kubeadm)
企业级 Java AI Agent 任务编排、安全审批、RAG 与全链路审计平台
本地、开源的推理框架，支持 Claude 和 Codex，包含 48 个编写好的系统，仅在需要更深层推理时选用。Local, open-source reasoning framework for Claude and Codex, with 48 authored systems selected only when deeper reasoning helps.
使用纯 C 从零构建 LLM 推理引擎，不依赖任何框架。Build an LLM inference engine from scratch in pure C with no frameworks.
AI 时代的工具联盟：可追溯的知识（Nexus·Archon）、可问责的审查与治理（Arbiter·Observer）、可理解的变更质量（Adept·Probe）。AI 构建，你来理解。An alliance of tools for the AI era: grounded knowledge (Nexus·Archon), accountable review & governance (Arbiter·Observer), and comprehension & mutation quality (Adept·Probe). AI builds it — you understand it.
一个工作流框架，适配所有编码 agent。通过与工具无关的核心，将你的 AI 编码规范安装到 Claude Code、Cursor、GitHub Copilot、Gemini CLI、Codex 和 Windsurf。Apache 2.0。One workflow framework, every coding agent. Install your AI-coding discipline into Claude Code, Cursor, GitHub Copilot, Gemini CLI, Codex, and Windsurf from one tool-agnostic core. Apache 2.0.