Introducing Swarmcore: A Scalable Multi-Agent Framework in Python

Swarmcore is an open-source library designed for executing multi-agent workflows in Python. This library allows developers to run agents sequentially or in parallel. It includes a context management system ensuring that outputs from one agent do not interfere with another, which proves beneficial in complex workflows.

To define agents, you can set them up like so:

planner = Agent(name="planner", instructions="Break the topic into research questions.", model="ollama/llama3") researcher = Agent(name="researcher", instructions="Research the topic in depth.", model="ollama/llama3")

You can chain these agents using symbols: '>>' for sequential execution and '|' for parallel execution. An example chain might look like this:

flow = planner >> (researcher | critic) >> (verifier | evaluator) >> writer result = asyncio.run(Swarm(flow=flow).run("AI agent trends in 2026"))

The library is currently available as a Python package and can be installed via:

pip install swarmcore

The creator is considering expanding this framework into a CLI-based tool and reports that it delivers results comparable to more established research frameworks like gemini deep research.