Search results for "human-in-the-loop"
A text-based user interface (TUI) client for interacting with MCP servers using Ollama. Features include agent mode, multi-server, model switching, streaming responses, tool management, human-in-the-l
Open-source multi-agent AI assistant powered by LangGraph, FastAPI & Next.js — 16+ agents, Human-in-the-Loop, MCP integration, voice TTS, RAG, 500+ metrics, 6 languages.
A framework for building, orchestrating and deploying AI agents and multi-agent workflows with support for Python and .NET.
Framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks.
AI Agent Framework, the Pydantic way
Build resilient language agents as graphs.
🔬 Harness Vibe Research with Self-evolving AI Scientists
Build autonomous AI agents in Python.
Build AI agents that actually do things. Synapse is an open-source platform for creating, connecting, and orchestrating AI agents powered by any LLM — local or cloud.
Build and run agents you can see, understand and trust.
ARIS ⚔️ (Auto-Research-In-Sleep) — Lightweight Markdown-only skills for autonomous ML research: cross-model review loops, idea discovery, and experiment automation. No framework, no lock-in — works wi
AG2 (formerly AutoGen): The Open-Source AgentOS.Join us at: https://discord.gg/sNGSwQME3x
Python Deep Agent framework built on top of Pydantic-AI, designed to help you quickly build production-grade autonomous AI agents with planning, filesystem operations, subagent delegation, skills, and
🐫 CAMEL: The first and the best multi-agent framework. Finding the Scaling Law of Agents. https://www.camel-ai.org
One-stop handbook for building, deploying, and understanding LLM agents with 60+ skeletons, tutorials, ecosystem guides, and evaluation tools.
A general-purpose coding agent that runs inside an NVIDIA OpenShell sandbox, orchestrated by Deep Agents and powered by NVIDIA Nemotron. The agent writes and executes code in an isolated, policy-gover
[GenAI Application Development Framework] 🚀 Build GenAI application quick and easy 💬 Easy to interact with GenAI agent in code using structure data and chained-calls syntax 🧩 Use Event-Driven Flow
Pocket Flow: 100-line LLM framework. Let Agents build Agents!
🛡⚔️AI-Powered Penetration Testing Framework with automated vulnerability scanning, multi-agent system, and compliance reporting🛡⚔️
AgenticX is a unified, production-ready multi-agent platform — Python SDK + CLI (agx) + Studio server + Machi desktop app. Features Meta-Agent orchestration, 15+ LLM providers, MCP Hub, hierarchical m
Unified framework for building enterprise RAG pipelines with small, specialized models
Self-evolving agent: grows skill tree from 3.3K-line seed, achieving full system control with 6x less token consumption
[NeurIPS 2024 D&B] GTA: A Benchmark for General Tool Agents & [arXiv 2026] GTA-2
3-tier agentic ChatOps (n8n + GPT-4o + Claude Code) implementing all 21 patterns from "Agentic Design Patterns" — solo operator managing 137 devices
🔥 An autonomous AI agent that runs your deep learning experiments 24/7 while you sleep. Zero-cost monitoring, Leader-Worker architecture, constant-size memory.
AI skills that turns coding agents into UiPath experts.
LLM-powered Agent Runtime with Dynamic DAG Planning & Concurrent Execution
Human-supervised AI code generation using Plan-Do-Check-Act methodology with TDD and refactoring. Works as Claude Code skill or standalone prompts.
🤖 The most comprehensive directory of AI agent frameworks, platforms, tools, and resources - hundreds of curated entries covering open-source, no-code, enterprise, and autonomous solutions. NEW Boil
The production runtime for AI agents. Schema in, API out. Built on PydanticAI + FastAPI.
AITP Research Charter and Protocol: a charter-first protocol, contract, and adapter surface for AI-assisted theoretical physics research.
Autonomous AI agent that researches viral content, generates posts, publishes them, measures engagement — and rewrites its own strategy based on what worked. Self-learning loop powered by LangGraph +
Automatically Update LLM-Agent Papers Daily using Github Actions (Update Every 12th hours)
Self-hosted autonomous AI agent — 9-layer cascade, Docker sandbox, encrypted vault, review/build/control plane, 1407+ tests
Hybrid cloud-local AI Employee that runs 24/7 on a cloud VM, monitors Gmail/WhatsApp, drafts responses, and queues approvals via git-synced Obsidian vault. Human-in-the-loop safety gates for email, so
Enable peer-to-peer collaboration between AI agents with human supervision for complex task coordination and decision-making.
ACR Control Plane: runtime control & governance for agentic AI (six-pillar enforcement).
An event-driven, async-first, step-based way to control the execution flow of AI applications like Agents.