GPT Researcher — Autonomous Research Report Agent

What it is

GPT Researcher is an open-source autonomous AI agent that produces comprehensive research reports from a single query. Given a topic, it plans sub-questions, searches multiple web sources, scrapes and summarizes relevant content, and synthesizes everything into a structured report with citations. The agent handles the entire research workflow that would otherwise require manual searching, reading, and writing.

GPT Researcher targets professionals, analysts, and teams who need well-researched reports without spending hours on manual web research. It works with OpenAI, Anthropic, and other LLM providers.

How it saves time or tokens

Manual research involves iterating between search engines, reading articles, taking notes, and synthesizing findings. GPT Researcher automates this entire loop. It generates 3-5 sub-questions from your main query, searches each one across multiple sources, extracts relevant passages, and compiles a coherent report. A research task that takes hours manually completes in minutes.

The agent uses focused sub-queries rather than one broad search, which produces more relevant results and reduces the need for follow-up searches.

How to use

1. Install GPT Researcher: pip install gpt-researcher. Set your OPENAI_API_KEY and optionally a search API key (Tavily, Serper, or Bing).
2. Define your research query as a plain text string. Optionally specify the report type (research_report, detailed_report, outline_report).
3. Run the researcher. It plans, searches, scrapes, and writes the report autonomously. The output is a Markdown document with inline citations.

Example

from gpt_researcher import GPTResearcher
import asyncio

async def main():
    researcher = GPTResearcher(
        query='What are the best practices for LLM evaluation in production?',
        report_type='research_report'
    )
    report = await researcher.conduct_research()
    print(report)

asyncio.run(main())

The agent autonomously breaks the query into sub-questions, searches the web, reads relevant pages, and produces a multi-section report with source URLs.

Related on TokRepo

• AI tools for research — Research automation and analysis tools
• AI tools for content — Content generation and writing tools

Common pitfalls

• GPT Researcher makes multiple LLM calls and web searches per report. A single detailed report can use significant tokens and API credits. Monitor costs for production use.
• Report quality depends heavily on search result quality. Configure a reliable search API (Tavily is recommended) for best results. Free search APIs may return lower-quality results.
• The agent scrapes web pages to extract content. Some websites block automated scraping. If key sources are behind paywalls or CAPTCHAs, those sources will be missing from the report.