User's Guide
To generate a report using Open Deep Research, the following steps are required:
- environmental preparation: Create a Python virtual environment and install the package (pip install open-deep-research)
- API Configuration: Setting up keys for search APIs like Tavily and writing models
- Select Model: The default combination uses Tavily search + Anthropic writing + OpenAI planning
- running example: Sample code execution via Jupyter Notebook
- Feedback Optimization: Request changes to the generated plan
- final product (of a project): Full report writing begins after confirmation of plan
The complete command line process includes steps such as compiling charts, setting thread parameters, entering research topics, and submitting feedback. The system provides detailed execution logs so that users can monitor the progress of report generation in real time.
This answer comes from the articleOpen Deep Research: LangChain's Open Source Intelligent Assistant for Deep ResearchThe
May not be reproduced without permission:AI productivity tools " How to generate research reports quickly with Open Deep Research?
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