Description
GPT Researcher is an open-source deep research agent designed to conduct in-depth research on any given task, providing detailed, factual, and unbiased research reports. Inspired by Plan-and-Solve and RAG papers, it addresses misinformation, speed, and reliability by offering stable performance and increased speed through parallelized agent work. The core functionality revolves around 'planner' and 'execution' agents. The planner generates research questions, while the execution agents gather relevant information from various sources.
The tool's architecture involves creating a task-specific agent based on a research query, generating questions to form an objective opinion, using a crawler agent to gather information, summarizing and source-tracking each resource, and filtering and aggregating summaries into a final research report. GPT Researcher supports web and local research, with the ability to generate reports exceeding 2,000 words. It also includes smart image scraping and filtering, AI-generated inline images, and the ability to aggregate over 20 sources for objective conclusions. The frontend is available in lightweight (HTML/CSS/JS) and production-ready (NextJS + Tailwind) versions.
GPT Researcher offers several key features, including the generation of detailed research reports using web and local documents, smart image scraping, and AI-generated inline images using Google Gemini. It supports JavaScript-enabled web scraping, maintains memory and context throughout research, and allows reports to be exported to PDF, Word, and other formats. The tool also supports MCP integration for connecting with specialized data sources and offers a multi-agent assistant built with LangGraph and AG2. Furthermore, it supports LangSmith for enhanced tracing and observability, and features an enhanced frontend for improved user experience. The tool is designed for individuals and organizations seeking accurate, unbiased, and factual information through AI.
GPT Researcher's Core Features
Generates detailed research reports
Smart image scraping and filtering
AI-generated inline images
Supports reports exceeding 2,000 words
Aggregates over 20 sources
JavaScript-enabled web scraping
Maintains memory and context
Exports reports to multiple formats
Supports MCP integration
Multi-agent assistant with LangGraph and AG2
LangSmith for enhanced tracing
Enhanced frontend for user experience
Deep Research workflow
Getting Started with GPT Researcher
Clone: Clone the project from GitHub.
Install dependencies: Install Python 3.11 or later and install dependencies using pip.
Configure: Set up API keys by exporting them or storing them in a .env file.
Execute: Run the server using the command provided.
Access: Visit the specified local address in your browser.
GPT Researcher's Use Cases
- In-depth research reports
- Competitive analysis
- Academic research
- Content creation
- Market analysis
- Information gathering
- Knowledge base creation
