How to Choose

GPT Researcher is a powerful autonomous research agent designed to enhance and streamline your research processes. Whether you're a developer looking to integrate research capabilities into your project or an end-user seeking a comprehensive research solution, GPT Researcher offers flexible options to meet your needs.

We envision a future where AI agents collaborate to complete complex tasks, with research being a critical step in the process. GPT Researcher aims to be your go-to agent for any research task, regardless of complexity. It can be easily integrated into existing agent workflows, eliminating the need to create your own research agent from scratch.

Options

GPT Researcher offers multiple ways to leverage its capabilities:

1. GPT Researcher PIP agent: Ideal for integrating GPT Researcher into your existing projects and workflows.
2. Backend: A backend service to interact with the frontend user interfaces, offering advanced features like detailed reports.
3. Multi Agent System: An advanced setup using LangGraph, offering the most comprehensive research capabilities.
4. Frontend: Several front-end solutions depending on your needs, including a simple HTML/JS version and a more advanced NextJS version.

Usage Options

1. PIP Package

The PIP package is ideal for leveraging GPT Researcher as an agent in your preferred environment and code.

Pros:

• Easy integration into existing projects
• Flexible usage in multi-agent systems, chains, or workflows
• Optimized for production performance

Cons:

• Requires some coding knowledge
• May need additional setup for advanced features

Installation:

pip install gpt-researcher

System Requirements:

• Python 3.10+
• pip package manager

Learn More: PIP Documentation

2. End-to-End Application

For a complete out-of-the-box experience, including a sleek frontend, you can clone our repository.

Pros:

• Ready-to-use frontend and backend services
• Includes advanced use cases like detailed report generation
• Optimal user experience

Cons:

• Less flexible than the PIP package for custom integrations
• Requires setting up the entire application

Getting Started:

1. Clone the repository: git clone https://github.com/assafelovic/gpt-researcher.git
2. Follow the installation instructions

System Requirements:

• Git
• Python 3.10+
• Node.js and npm (for frontend)

Advanced Usage Example: Detailed Report Implementation

3. Multi Agent System with LangGraph or AG2

We've collaborated with LangChain and AG2 to support multi-agent workflows with GPT Researcher, offering the most complex and comprehensive version of GPT Researcher.

Pros:

• Very detailed, customized research reports
• Inner AI agent loops and reasoning

Cons:

• More expensive and time-consuming
• Heavyweight for production use

This version is recommended for local, experimental, and educational use. We're working on providing a lighter version soon!

System Requirements:

• Python 3.10+
• LangGraph or AG2 library

Learn More:

• GPT Researcher x LangGraph
• GPT Researcher x AG2

Comparison Table

Please note that all options have been optimized and refined for production use.

Deep Dive

To learn more about each of the options, check out these docs and code snippets:

1. PIP Package:

   • Install: pip install gpt-researcher
   • Integration guide

2. End-to-End Application:

   • Clone the repository: git clone https://github.com/assafelovic/gpt-researcher.git
   • Installation instructions

3. Multi-Agent System:

   • Multi-Agents code
   • LangGraph documentation
   • AG2 documentation
   • Blog

Versioning and Updates

GPT Researcher is actively maintained and updated. To ensure you're using the latest version:

• For the PIP package: pip install --upgrade gpt-researcher
• For the End-to-End Application: Pull the latest changes from the GitHub repository
• For the Multi-Agent System: Check the documentation for compatibility with the latest LangGraph and AG2 versions

Troubleshooting and FAQs

For common issues and questions, please refer to our FAQ section in the documentation.