ToolUniverse  by mims-harvard

Platform for building AI scientists from any LLM

Created 7 months ago
467 stars

Top 65.1% on SourcePulse

GitHubView on GitHub
Project Summary

Summary

ToolUniverse provides an ecosystem for building AI scientists by standardizing the integration of any large language model (LLM) with over 600 scientific tools, including ML models, datasets, and APIs. It democratizes AI-driven scientific discovery by enabling users to create custom AI scientists for tasks like data analysis and experimental design without requiring LLM retraining.

How It Works

The system employs an "AI-Tool Interaction Protocol" to standardize how AI models identify and invoke tools. It supports universal LLM compatibility, abstracting diverse tool capabilities behind a unified interface. This allows any LLM to function as a research scientist, composing and executing tools for complex scientific workflows.

Quick Start & Requirements

  • Installation: pip install tooluniverse or uv pip install tooluniverse.
  • Prerequisites: A GPU is required for the embedding-based Tool_Finder.
  • Resources: Links to a 5-minute Quick Start Tutorial and comprehensive Installation/Getting Started guides are available.

Highlighted Details

  • Integrates over 600 scientific tools: ML models, datasets, APIs, and Python packages.
  • Universal AI model support: Compatible with major LLMs (GPT, Claude, Gemini, Qwen) and open models.
  • Flexible integration: Python SDK, MCP server, and various CLI integrations (Claude Desktop, Gemini CLI, etc.).
  • Enables tool composition for sequential/parallel execution in self-directed scientific workflows.

Maintenance & Community

  • Community: Active Slack and WeChat communities, with presence on LinkedIn and X.
  • Contacts: Key contributors and contacts include Shanghua Gao and Marinka Zitnik.

Licensing & Compatibility

  • License: The provided README does not explicitly state a software license.
  • Compatibility: No specific compatibility restrictions are mentioned beyond general Python environment requirements.

Limitations & Caveats

A GPU is mandatory for the embedding-based Tool_Finder functionality. The absence of a clearly stated software license presents a significant adoption blocker, requiring clarification before commercial or widespread use.

Health Check
Last Commit

19 hours ago

Responsiveness

Inactive

Pull Requests (30d)
6
Issues (30d)
7
Star History
263 stars in the last 30 days

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