agentskillexchange Run configurable multi-source deep research passes with Open Deep Research
Use Open Deep Research when an agent should run a configurable research job that searches, compresses, synthesizes, and writes a cited report across multiple model and search backends.
Prerequisites
Python, uv, model API credentials, one or more supported search tools
Installation
Use the upstream install or setup path that matches your environment:
- git clone https://github.com/langchain-ai/open_deep_research.git
- uv venv
- uv sync
- uv pip install -r pyproject.toml
Requirements and caveats from upstream:
- uvx --refresh --from "langgraph-cli[inmem]" --with-editable . --python 3.11 langgraph dev --allow-blocking
- Open Deep Research supports a wide range of LLM providers via the init_chat_model() API. It uses LLMs for a few different tasks. See the below mo...
- Note: the selected model will need to support structured outputs and tool calling.
Basic usage or getting-started notes:
cp .env.example .env
This will open the LangGraph Studio UI in your browser.
🚀 API: http://127.0.0.1:2024
Extracted from upstream docs: https://raw.githubusercontent.com/langchain-ai/open_deep_research/HEAD/README.md