Neosapiens: Run multi-agent tasks from Python

Understand the project

Practical overview

Use the documented interface when prototyping a Python workflow that sends a task to an AI-agent team.

Python developers exploring multi-agent task execution.
Builders prototyping a task runner that delegates a natural-language prompt to a team of AI agents.

Before you choose

The README documents installation with pip. The GitHub repository specifies an MIT license.

The documented interface is a Python function that accepts a natural-language task.
The sample demonstrates a call and printed return value, but does not establish a particular task result.
Tool processing, routing, memory, and swarm-network logic are listed as TODOs rather than documented implemented features.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Follow the README's documented installation and Python call pattern for submitting a task to an agent swarm.

Install the packages with the command below.
Documented command
```
pip install -U swarms neo-sapiens
```
In Python, import run_swarm from neo_sapiens.
Call run_swarm with a natural-language task, assign the return value, and print it.

The documented pattern returns a value from the `run_swarm` call for printing.

The README provides an example, not evidence of a verified run or guaranteed output.
The documentation does not specify model credentials or provider configuration.
Tool processing, routing, memory, and swarm-network logic appear in the README's TODO list.

Evidence and transparency

Source record details

Source availability: Active
Sources checked: 13 October 2026
Original website title: kyegomez/NeoSapiens · Official homepage title · retained in its source language