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:
- GPT Researcher PIP agent: Ideal for integrating GPT Researcher into your existing projects and workflows.
- Backend: A backend service to interact with the frontend user interfaces, offering advanced features like detailed reports.
- Multi Agent System: An advanced setup using LangGraph, offering the most comprehensive research capabilities.
- 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:
- Clone the repository:
git clone https://github.com/assafelovic/gpt-researcher.git - 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
We've collaborated with LangChain to support multi-agents with LangGraph and 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 library
Learn More: GPT Researcher x LangGraph
Comparison Table
| Feature | PIP Package | End-to-End Application | Multi Agent System |
|---|---|---|---|
| Ease of Integration | High | Medium | Low |
| Customization | High | Medium | High |
| Out-of-the-box UI | No | Yes | No |
| Complexity | Low | Medium | High |
| Best for | Developers | End-users | Researchers/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:
PIP Package:
- Install:
pip install gpt-researcher - Integration guide
- Install:
End-to-End Application:
- Clone the repository:
git clone https://github.com/assafelovic/gpt-researcher.git - Installation instructions
- Clone the repository:
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 LangChain and LangGraph versions
Troubleshooting and FAQs
For common issues and questions, please refer to our FAQ section in the documentation.