Deep Research is an open source AI research assistant project released by dzhng on GitHub, and its core technology is characterized by the integration of three types of key components: search engine interface to support the acquisition of raw data, intelligent crawlers to achieve web content crawling, and a large language model is responsible for the processing of information and optimization of strategies. This three-in-one architecture gives it a unique iterative research capability, which enables it to realize in-depth knowledge mining through the closed-loop process of "query generation - result acquisition - in-depth analysis". The project pays special attention to code simplicity, keeping the core functions within 500 lines, which not only ensures technical transparency, but also reduces the threshold of secondary development.
From the technical implementation point of view, the system runs in a Node.js environment, and developers can quickly deploy the research environment by managing dependencies through npm. The environment variable configuration system supports flexible docking of different search engine APIs, and this modularized design provides the research agent with good scalability. The project also provides a commercial product Aomni for enterprise users, which is specifically optimized for sales and GTM (Go-To-Market) scenarios.
This answer comes from the articleDeep Research: an AI-based deep research assistant that provides efficient research tools and report generation capabilitiesThe
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