Skip to main content

A framework for building distributed evolvable multi-agent system.

This project has been quarantined.

PyPI Admins need to review this project before it can be restored. While in quarantine, the project is not installable by clients, and cannot be being modified by its maintainers.

Read more in the project in quarantine help article.

Project description


1 What is PantheonOS?

PantheonOS is an evolvable and privacy-preserving multi-agent framework designed to reconcile generality with domain specificity. PantheonOS automates, scales and accelerates data sciences, with a particular focus on end-to-end single cell biology analyses. Cruicially, PantheonOS leverages agentic code evolution to optimize state-of-the-art and nascent algorithms, achieving super-human performance on specialized scientific tasks.

Key Highlights

  • Evolvable — Pantheon-Evolve module enables agents to improve algorithms and code through genetic-algorithm-driven agentic code evolution
  • Multi-Agent Teams — PantheonTeam, Sequential, Swarm, Mixture-of-Agents (MoA), and AgentAsTool team patterns for flexible orchestration
  • Distributed Architecture — NATS-based messaging for scalable, fault-tolerant deployments across machines
  • Friendly Interfaces — Interactive CLI (pantheon cli) and Chatroom UI (pantheon ui)
  • Pantheon Store — A community marketplace with 1,000+ curated agents, teams, and skills for biomedical AI, installable via UI or CLI

2 Quick Start & Community

Play with our Web UI!
Download the latest desktop app release.
Browse 1,000+ agents, teams, and skills!
pip install pantheon-agents
Join our Slack community!
Join our Discord community!

3 Installation

Desktop App

Download the latest Pantheon Desktop app:

Open the release page to download the latest version for your platform.

Using uv (Recommended)

uv is a fast Python package manager that handles dependencies efficiently.

# Install uv (if not already installed)
# macOS/Linux
curl -LsSf https://astral.sh/uv/install.sh | sh
# Windows
powershell -c "irm https://astral.sh/uv/install.ps1 | iex"

# Clone and install
git clone https://github.com/aristoteleo/PantheonOS.git
cd PantheonOS
uv sync

# With optional dependencies
uv sync --extra knowledge  # RAG/vector search support
uv sync --extra claw       # PantheonClaw mobile gateway channels
uv sync --extra r          # R language support (requires R installed)

Using pip

# Basic installation
pip install pantheon-agents

# With optional dependencies
pip install "pantheon-agents[knowledge]"  # RAG/vector search support
pip install "pantheon-agents[claw]"       # PantheonClaw mobile gateway channels

Development Installation

git clone https://github.com/aristoteleo/PantheonOS.git
cd PantheonOS
uv sync --extra dev --extra knowledge

# Run tests
uv run pytest tests/

Using Docker

Docker Pulls

Run Pantheon in a containerized environment with everything pre-configured:

# Pull the image
docker pull nanguage/pantheon-agents:latest

# Run in standalone mode (for local use)
docker run -it --rm \
  -e PANTHEON_MODE=standalone \
  -v $(pwd)/workspace:/workspace \
  -p 8080:8080 \
  nanguage/pantheon-agents:latest

After startup, copy the displayed connection URL to your browser and start using Pantheon!

For detailed Docker usage, deployment modes, and configuration options, see the Docker documentation.

4 Usage

CLI Mode

# Start the interactive REPL
pantheon cli

Chatroom UI

# Start the multi-agent chatroom
pantheon ui --auto-start-nats --auto-ui

API Usage

Please refer to our Documents for detailed API usage, including creating agents, using toolsets, and building teams.

5 Replayable Trajectories

Interactive replays of real multi-agent Pantheon sessions. Click any card to open the session step-by-step in the Pantheon UI — see every message, every file, every tool call.

E6 Mouse Embryo Tangram + 3D Visualization
🐭 E6 Mouse Embryo Tangram + 3D Visualization
Run Tangram deconvolution on E6.0 mouse embryo binned spatial transcriptomics (51,711 spots across 6 embryos, 16,732 shared genes) using the TOME atlas reference subset to timepoints 5.5/6.25 and 5 cell types (Epi, ExE, EmVE, PE, ExVE).
Immune Oncology Gene Panel Design
🧬 Immune Oncology Gene Panel Design
Design a 1000-plex human immune oncology gene profiling panel using multi-agent collaboration.
3D Human Fetal Heart Disease Gene Pattern
🫀 3D Human Fetal Heart Disease Gene Pattern
Map congenital heart disease genes onto a 3D PCW12 human fetal heart using MERFISH spatial transcriptomics and scRNA-seq.
ATAC Spatial Mapping via MOSCOT
🗺️ ATAC Spatial Mapping via MOSCOT
Spatially map fetal heart snATAC-seq onto MERFISH 3D coordinates using MOSCOT optimal transport.
Spatial Ligand-Receptor Disease Analysis
🧬 Spatial Ligand-Receptor Disease Analysis
Run spatial ligand-receptor (CCI) interaction analysis on MOSCOT-imputed disease gene data using the Spateo spatial_cci skill.
Heart MERFISH Data Overview
🫀 Heart MERFISH Data Overview
Exploratory data overview of fetal heart MERFISH spatial transcriptomics.
Multi-Channel Cell Segmentation
🧬 Multi-Channel Cell Segmentation
Compare cell segmentation tools on a 3-channel embryo image (membrane / DAPI / brightfield).
More trajectories coming soon — browse the full dataset on HuggingFace →

6 Contributing

Contributions of all types are more than welcome! Whether it's publishing skills to the Pantheon Store or contributing code, feel free to check out our GitHub Issues to dive in.

License

This project is BSD 2-Clause licensed.

Copyright © 2026 Qiu Lab.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

pantheon_agents-0.6.0-py3-none-any.whl (1.6 MB view details)

Uploaded Python 3

File details

Details for the file pantheon_agents-0.6.0-py3-none-any.whl.

File metadata

File hashes

Hashes for pantheon_agents-0.6.0-py3-none-any.whl
Algorithm Hash digest
SHA256 9806353a73c7bdcfa6e5035023e83d6821ff0a0d2f8a829f3af05670f98fa404
MD5 09d340f55cb9174606b750eda3fb21f5
BLAKE2b-256 a6e325b8c73ed132d2306a071c08760ea457ec71b146371fb53d75100f83e280

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page