Multi-Agent-Scientist

Multi-Agent Scientist The Multi-Agent Scientist is an AI pipeline designed to automate the process of generating scientific research ideas and drafting patent applications. It consists of four interconnected agents that work sequentially to produce novel scientific ideas and corresponding patents based on the latest research literature.

Table of Contents

1. Overview
2. Features
3. Project Structure
4. Installation
5. Prerequisites
6. Steps
7. Usage
8. Customization

Agents and Their Functionality

1. Literature Review Agent

2. Scientific Research Agent

3. Patent Search Agent

4. Patent Writing Agent

   Dependencies License Acknowledgments Contact Overview The Multi-Agent Scientist leverages OpenAI's o1-preview and o1-mini models to process and generate text, and utilizes APIs from arXiv, PubMed, and patent databases. The pipeline includes:

Literature Review Agent: Gathers and summarizes relevant scientific papers. Scientific Research Agent: Generates new scientific ideas based on the literature review. Patent Search Agent: Checks the originality of each idea by searching existing patents. Patent Writing Agent: Drafts patent applications for original ideas.

Features Automated Literature Review: Fetches and summarizes recent scientific papers on a chosen topic. Idea Generation: Produces novel scientific research ideas using AI language models. Patent Originality Check: Searches patent databases to verify the uniqueness of generated ideas. Automated Patent Drafting: Creates patent application documents for original ideas. Project Structure

Installation

Prerequisites

Python 3.7 or higher OpenAI account with access to o1-preview or o1-mini models NCBI Entrez email registration for PubMed API access API keys for patent databases (if applicable)

Agents and Their Functionality

1. Literature Review Agent

Purpose: Collects and summarizes scientific papers relevant to the chosen topic.

Data Sources: arXiv, PubMed Functionality: Searches for papers using the specified query. Summarizes abstracts using OpenAI's language models. Compiles summaries into a cohesive literature review. Output: outputs/literature_review.md

2. Scientific Research Agent

Purpose: Generates new scientific ideas based on the literature review.

Input: The literature review from the first agent. Functionality: Analyzes the literature review to identify gaps and opportunities. Generates novel ideas using AI models. Output: data/ideas.json

3. Patent Search Agent

Purpose: Determines the originality of generated ideas by searching existing patents.

Input: List of generated ideas. Functionality: Searches patent databases (e.g., USPTO, EPO, Google patents) for each idea. Marks ideas as original ('y') or not ('n'). Output: Updated data/ideas.json with originality status.

4. Patent Writing Agent

Purpose: Drafts patent applications for original ideas.

Acknowledgments

OpenAI: For providing powerful language models. arXiv: For access to pre-print scientific papers. PubMed: For access to biomedical literature. Patent Offices: For providing patent search APIs.

Note: This project is intended for educational and research purposes only.