Open Deep Research

🔬 Open Deep Research

Deep research has broken out as one of the most popular agent applications. This is a simple, configurable, fully open source deep research agent that works across many model providers, search tools, and MCP servers. It's performance is on par with many popular deep research agents ([see Deep Research Bench leaderboard](https://huggingface.co/spaces/Ayanami0730/DeepResearch-Leaderboard)).

🔥 Recent Updates

**August 14, 2025**: See our free course [here](https://academy.langchain.com/courses/deep-research-with-langgraph) (and course repo [here](https://github.com/langchain-ai/deep_research_from_scratch)) on building open deep research.

**August 7, 2025**: Added GPT-5 and updated the Deep Research Bench evaluation w/ GPT-5 results.

**August 2, 2025**: Achieved #6 ranking on the [Deep Research Bench Leaderboard](https://huggingface.co/spaces/Ayanami0730/DeepResearch-Leaderboard) with an overall score of 0.4344.

**July 30, 2025**: Read about the evolution from our original implementations to the current version in our [blog post](https://rlancemartin.github.io/2025/07/30/bitter_lesson/).

**July 16, 2025**: Read more in our [blog](https://blog.langchain.com/open-deep-research/) and watch our [video](https://www.youtube.com/watch?v=agGiWUpxkhg) for a quick overview.

🚀 Quickstart

1. Clone the repository and activate a virtual environment:

git clone https://github.com/langchain-ai/open_deep_research.git
cd open_deep_research
uv venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate

1. Install dependencies:

uv sync
# or
uv pip install -r pyproject.toml

1. Set up your .env file to customize the