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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:

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  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:

Comparison Table​

FeaturePIP PackageEnd-to-End ApplicationMulti Agent System
Ease of IntegrationHighMediumLow
CustomizationHighMediumHigh
Out-of-the-box UINoYesNo
ComplexityLowMediumHigh
Best forDevelopersEnd-usersResearchers/Experimenters

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:

  2. End-to-End Application:

  3. Multi-Agent System:

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.