Open source deep researcher that also thinks based on `OpenAI DeepResearch. This automates online research using DeepSeek-R1 via Nebius AI Studio and Exa search APIs. It continuously generates search queries, extracts relevant content, evaluates information and produces a comprehensive research report based on all relevant information collected.
Watch demo video on Youtube
You can run this deep researcher using this Google Colab
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Automated Research: Uses AI to generate search queries and evaluate results.
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Iterative Search: Runs multiple iterations to refine and improve the quality of results.
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Content Extraction & Evaluation: Identifies and extracts relevant information from search results.
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Final Report Generation: Summarizes findings into a well-structured report.
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Gradio UI: Provides a user-friendly web interface for easy interaction.
- User can choose any LLM models available via Nebius Studio to power DeepThink-Researcher.
- Increase the number of iterations to refine responses further.
- Extend the text/context length from 2,000 to 5,000 or even 20,000 words/characters — but this will increase processing time and API costs.
- Optimize response times for production and public use to enhance performance.
- Export whole notebook code into hosted python web app using tools like reflex.dev or streamlit.
- Add option for users to download final report.
To run this project, install the required dependencies:
!pip install nest_asyncio gradio aiohttp openai exa_py
Before running the researcher, set up your API keys in the notebook:
NEBIUS_API_KEY = "your_nebius_api_key" # Replace with your Nebius API key
EXA_API_KEY = "your_exa_api_key" # Replace with your EXA API key
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User Query: The research topic or question you want to investigate.
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Iteration Limit: The maximum number of iterations the AI should perform while refining search queries.
Try out the following example queries:
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"What are the latest advancements in quantum computing?"
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"How does intermittent fasting impact metabolism?"
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"Best practices for deploying large-scale AI models."
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"Comparison of cloud AI providers: AWS vs. GCP vs. Azure."
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async_research()
: Handles the asynchronous execution of research. -
call_nebius_async()
: Calls Nebius AI for generating responses. -
perform_search_async()
: Uses Exa API to fetch search results. -
is_page_useful_async()
: Evaluates the relevance of a webpage. -
extract_relevant_context_async()
: Extracts meaningful content from pages. -
generate_final_report_async()
: Compiles all information into a final research report. -
gradio_run()
: Wraps everything into a Gradio UI.
Contributions are welcome! Please feel free to open issues or submit pull requests.
This project is licensed under the MIT License.
- This researcher is a extended fork of OpenDeepResearcher
- DeepSeek Model is used via Nebius AI Studio