aden-hive / hive

English | 简体中文 | Español | हिन्दी | Português | 日本語 | Русский | 한국어 Overview Generate a swarm of worker agents with a coding agent(queen) that control them. Define your goal through conversation with hive queen, and the framework generates a node graph with dynamically created connection code. When things break, the framework captures failure data, evolves the agent through the coding agent, and redeploys. Built-in human-in-the-loop nodes, browser use, credential management, and real-time monitoring give you control without sacrificing adaptability. Visit adenhq.com for complete documentation, examples, and guides. Who Is Hive For? Hive is designed for developers and teams who want to build many **autonomous AI agents** fast without manually wiring complex workflows. Hive is a good fit if you: • Want AI agents that **execute real business processes**, not demos • Need **fast or high volume agent execution** over open workflow • Need **self-healing and adaptive agents** that improve over time • Require **human-in-the-loop control**, observability, and cost limits • Plan to run agents in **production environments** Hive may not be the best fit if you’re only experimenting with simple agent chains or one-off scripts. When Should You Use Hive? Use Hive when you need: • Long-running, autonomous agents • Strong guardrails, process, and controls • Continuous improvement based on failures • Multi-agent coordination • A framework that evolves with your goals Quick Links • **Documentation** - Complete guides and API reference • **Self-Hosting Guide** - Deploy Hive on your infrastructure • **Changelog** - Latest updates and releases • **Roadmap** - Upcoming features and plans • **Report Issues** - Bug reports and feature requests • **Contributing** - How to contribute and submit PRs Quick Start Prerequisites • Python 3.11+ for agent development • An LLM provider that powers the agents • **ripgrep (optional, recommended on Windows):** The tool uses ripgrep for faster file search. If not installed, a Python fallback is used. On Windows: or > **Windows Users:** Native Windows is supported via and . Run these in PowerShell 5.1+. WSL is also an option but not required. Installation > **Note** > Hive uses a workspace layout and is not installed with . > Running from the repository root will create a placeholder package and Hive will not function correctly. > Please use the quickstart script below to set up the environment. This sets up: • **framework** - Core agent runtime and graph executor (in ) • **aden_tools** - MCP tools for agent capabilities (in ) • **credential store** - Encrypted API key storage ( ) • **LLM provider** - Interactive default model configuration • All required Python dependencies with • Finally, it will open the Hive interface in your browser > **Tip:** To reopen the dashboard later, run from the project directory. Build Your First Agent Type the agent you want to build in the home input box. The queen is going to ask you questions and work out a solution with you. Use Template Agents Click "Try a sample agent" and check the templates. You can run a template directly or choose to build your version on top of the existing template. Run Agents Now you can run an agent by selecting the agent (either an existing agent or example agent). You can click the Run button on the top left, or talk to the queen agent and it can run the agent for you. Features • **Browser-Use** - Control the browser on your computer to achieve hard tasks • **Parallel Execution** - Execute the generated graph in parallel. This way you can have multiple agents completing the jobs for you • **Goal-Driven Generation** - Define objectives in natural language; the coding agent generates the agent graph and connection code to achieve them • **Adaptiveness** - Framework captures failures, calibrates according to the objectives, and evolves the agent graph • **Dynamic Node Connections** - No predefined edges; connection code is generated by any capable LLM based on your goals • **SDK-Wrapped Nodes** - Every node gets shared memory, local RLM memory, monitoring, tools, and LLM access out of the box • **Human-in-the-Loop** - Intervention nodes that pause execution for human input with configurable timeouts and escalation • **Real-time Observability** - WebSocket streaming for live monitoring of agent execution, decisions, and node-to-node communication Integration Hive is built to be model-agnostic and system-agnostic. • **LLM flexibility** - Hive Framework is designed to support various types of LLMs, including hosted and local models through LiteLLM-compatible providers. • **Business system connectivity** - Hive Framework is designed to connect to all kinds of business systems as tools, such as CRM, support, messaging, data, file, and internal APIs via MCP. Why Aden Hive focuses on generating agents that run real business processes rather than generic agents. Instead of requiring you to manually design workflows, define agent interactions, and handle failures reactively, Hive flips the paradigm: **you describe outcomes, and the system builds itself**—delivering an outcome-driven, adaptive experience with an easy-to-use set of tools and integrations. The Hive Advantage | Traditional Frameworks | Hive | | -------------------------- | -------------------------------------- | | Hardcode agent workflows | Describe goals in natural language | | Manual graph definition | Auto-generated agent graphs | | Reactive error handling | Outcome-evaluation and adaptiveness | | Static tool configurations | Dynamic SDK-wrapped nodes | | Separate monitoring setup | Built-in real-time observability | | DIY budget management | Integrated cost controls & degradation | How It Works • **Define Your Goal** → Describe what you want to achieve in plain English • **Coding Agent Generates** → Creates the agent graph, connection code, and test cases • **Workers Execute** → SDK-wrapped nodes run with full observabi…