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| # 🔍 Open DeepResearch | |
|  | |
| ## Overview | |
| Open DeepResearch is a powerful research assistant that leverages AI to conduct comprehensive research on any topic. It automates the process of gathering, analyzing, and synthesizing information from multiple sources to generate detailed reports with proper citations. | |
| ## Features | |
| - 🤖 AI-powered search query generation | |
| - 🌐 Automated web searching and content extraction | |
| - 📊 Smart relevance filtering | |
| - 📝 Comprehensive report generation with citations | |
| - 🔄 Iterative research refinement | |
| - 📱 User-friendly Streamlit interface | |
| ## Requirements | |
| You'll need API keys from: | |
| - [OpenRouter](https://openrouter.ai/keys) | |
| - [SerpAPI](https://serpapi.com/manage-api-key) | |
| - [Jina](https://jina.ai/api-key) | |
| ## Installation | |
| ```bash | |
| git clone https://github.com/yourusername/DeepResearch_App.git | |
| cd DeepResearch_App | |
| pip install -r requirements.txt | |
| ``` | |
| ## Usage | |
| 1. Launch the app: | |
| ```bash | |
| streamlit run app.py | |
| ``` | |
| 2. Configure your API keys in the sidebar | |
| 3. Enter your research query | |
| 4. Set the number of research iterations | |
| 5. Click "Start Research" and wait for your detailed report | |
| ## How It Works | |
| 1. **Query Generation**: AI creates targeted search queries based on your topic | |
| 2. **Web Search**: Automated search across multiple sources | |
| 3. **Content Analysis**: Relevant information extraction and filtering | |
| 4. **Report Generation**: Synthesized findings with proper citations | |
| 5. **Iterative Refinement**: Additional searches based on gaps in information | |
| ## Contributing | |
| Contributions are welcome! Please feel free to submit a Pull Request. | |
| ## License | |
| This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details. | |