Summary

Universal Deep Research (UDR) is a prototype system designed for AI-powered research automation, addressing the complexity of information gathering and synthesis. It combines user-defined strategies, intelligent web search, content analysis, and LLM-driven report generation. Targeting researchers and power users, UDR aims to streamline complex research workflows by automating these intricate tasks, providing a more efficient and insightful approach to knowledge discovery.

How It Works

The system comprises a FastAPI backend service and a Next.js frontend application. The backend orchestrates core research logic, including web scanning and LLM integration, while the frontend provides an interactive user interface for query management and result visualization. Its novel approach combines user-defined strategies with intelligent web search and content analysis, leveraging configurable LLM backends and real-time progress updates for a dynamic, automated research experience.

Quick Start & Requirements

To run the prototype, both backend and frontend services must be started.

• Backend: Navigate to backend/ and follow backend/README.md for Python environment setup, API key configuration, and server startup commands (e.g., launch_server.sh).
• Frontend: Navigate to frontend/ and follow frontend/README.md for Node.js dependency installation, environment configuration, and development server startup (e.g., npm run dev).
• Access the application via http://localhost:3000.
• Prerequisites: Python 3.8+, Node.js 18+, API keys for LLM providers (e.g., NVIDIA NGC, OpenAI), and a Tavily API key for web search functionality.

Highlighted Details

• Intelligent Research: Supports user-configurable research strategies for tailored exploration.
• Real-time Progress: Provides live updates during research execution and report generation.
• Interactive Interface: Features a modern web UI for managing research queries and visualizing results.
• Multi-Model Support: Allows configuration of various LLM backends for flexibility.

Maintenance & Community

No specific details regarding contributors, community channels (Discord/Slack), sponsorships, or roadmaps are provided in the README.

Licensing & Compatibility

The README does not specify a license type or mention compatibility notes for commercial use or closed-source linking.

Limitations & Caveats

This project is explicitly a research demonstration prototype and should not be used for production purposes. It contains experimental features and research-grade implementations, indicating potential instability or incomplete functionality.