Open Deep Research Agent - AI RAG and Search Tool

Overview

Open Deep Research Agent is an open‑source AI agent project that focuses on conducting in‑depth, factual research by separating high‑level planning from low‑level research execution. The agent architecture intentionally splits a planner (which produces stepwise research plans and subtasks) from researchers/executors (which perform retrieval, verification, and synthesis), enabling more controlled multi-step investigations and detailed report generation. According to the project's GitHub repository, the design targets research workflows that require iterative retrieval, model-based reasoning, and traceable outputs. The repository positions the project in the RAG and Search space: it combines retrieval mechanisms with reasoning models to produce lengthy, citation-aware reports rather than short conversational answers. Because it is open source, teams can inspect, adapt, and extend the planner and researcher components, swap retrieval backends or LLMs, and integrate custom evaluation or export routines. For full implementation details, runtime options, and example workflows, see the project's README on GitHub: https://github.com/nickscamara/open-deep-research.

Installation

Install via pip:

git clone https://github.com/nickscamara/open-deep-research.git

cd open-deep-research

pip install -r requirements.txt

cat README.md # follow project README for runtime configuration and example runs

Key Features

• Planner/Researcher separation: planner generates stepwise research plans, researchers execute retrieval and verification.
• Reasoning-model integration: uses models to synthesize evidence and produce chain-of-thought style justifications.
• Retrieval-augmented workflows: combines search/retrieval with model reasoning for factual grounding.
• Structured report generation: produces multi-section reports with citations and evidence traces.
• Extensible connectors: designed to allow swapping retrieval backends and model providers via configuration.

Community

Development and discussion occur on the project's GitHub repository (issues and pull requests used for feedback and contributions). The public repository provides issue tracking, contribution guidelines, and a place to file bugs or request features. For up-to-date activity, contributors, and recent commits, check the GitHub project page: https://github.com/nickscamara/open-deep-research.

Key Information

• Category: RAG and Search
• Type: AI RAG and Search Tool