Automate a multi-step business process using AI agents that work in parallel and recover from failures.
Add human-in-the-loop checkpoints where a person must approve before agents continue a workflow.
Track AI agent costs and audit trails across a long-running automated task.
Uses a quickstart script instead of pip install, requires API keys for your chosen LLM provider.
Hive is a Python framework for running multiple AI agents together on complex, long-running tasks in production environments. A single AI agent can handle personal tasks reasonably well, but when you need to automate a real business process that involves many steps, decisions, and potential failures, a single agent often falls apart. Hive provides the layer that coordinates groups of agents, keeps track of what has happened, and recovers from failures without losing progress. The framework works by taking a goal or workflow description and automatically generating a graph of tasks, then assigning specialized agents to run those tasks in parallel where possible. This graph-based approach means the system has a clear map of what needs to happen and in what order, rather than having agents improvise their way through a process. Memory is built in so that context from earlier steps carries forward to later ones, and the memory evolves as the project progresses. Hive is model-agnostic, meaning it works with language models from OpenAI, Anthropic, and Google Gemini. You pick which model powers your agents, and Hive handles the coordination around them. It also includes tools for browser control, file search, and other general compute tasks that agents may need to complete real-world workflows. For teams that need oversight, Hive supports human-in-the-loop checkpoints where a person can review or approve before the agents continue. It also tracks costs, maintains audit trails, and exposes observability data so you can see what agents are doing and how much they are spending. Installation uses a quickstart script rather than a standard pip install, due to how the project is structured with multiple internal packages. The setup script handles credentials, dependencies, and opens a browser dashboard. The project is backed by Aden, a Y Combinator company, and the README links to full documentation at their website.
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