ИИ-агенты
deep-research
Deep Research with any LLM: in-depth reports in minutes, with an SSE API and MCP server built in
★ 4,7 тыс. звёздMIT
Смотреть руководство →gpt-researcher — проект с открытым исходным кодом из категории «ИИ-агенты» от assafelovic (assafelovic/gpt-researcher на GitHub). У него 29 955 звёзд на GitHub и 4 095 форков, он распространяется по лицензии Apache-2.0 и последний раз обновлялся на GitHub 1 октября 2026.
An autonomous research agent that plans, searches and writes cited reports from any data source
Decide what you want to achieve with gpt-researcher and check the README on GitHub for requirements before installing.
Clone the repository from GitHub (or take the packaged install route in step 3 if the README offers one).
Follow the project's documented install commands — the Run section below lists the exact ones — and add any required API keys or models.
Work through the README's quickstart example end to end, then adapt it to your own project or data.
The agent breaks a question into sub-queries, searches them in parallel and synthesizes a report.
Output reports aggregate multiple sources with citations rather than a single model's memory.
A dedicated deep-research flow spends more time exploring for complex questions.
Point it at your own PDFs/documents to research private material, not just the web.
Works across LLM providers — configure the models you already have keys for.
Can run as an MCP server for agent hosts, and installs as a Claude Skill via npx skills.
Get the GPT Researcher source and examples.
git clone https://github.com/assafelovic/gpt-researcher.git
cd gpt-researcherInstall the requirements (or simply pip install gpt-researcher for library use), then set your LLM and search API keys in .env.
pip install -r requirements.txt
# library alternative: pip install gpt-researcherStart the app (or the Python example from the README), give it a research question and read the generated report.
# see the README 'Example Usage' for the exact Python snippetgpt-researcher is maintained by the assafelovic organization/account on GitHub, together with open-source contributors, in the public repository assafelovic/gpt-researcher.
Yes — the code is open source under the Apache-2.0 license. You can use, modify and redistribute it under that license's terms.
Yes — you need your own LLM API key and a web-search API key for the search provider you configure (Tavily is the common choice); the software itself is free and Apache-2.0 licensed.
Hosted deep-research tools are convenient but closed; GPT Researcher is self-hostable, provider-agnostic and scriptable, at the cost of your own keys and setup.
Clone the repository from GitHub, follow the install commands in the Run section (taken from the project's README), and complete the documented quickstart example before adapting it to your own use case.
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