LinkSeek

LinkSeek is a Next-Gen agentic app leveraging GraphRAG and NVIDIA cuGraph for optimized query execution, and provides easy-to-understand insights from complex relationships.

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LinkSeek: Agentic Graph Analysis App

Inspiration

Understanding global events through raw datasets can be overwhelming. LinkSeek was created to make event analysis and pattern discovery easier using graph-based AI. By leveraging GDELT data, we aimed to build a tool that helps users explore relationships, trends, and hidden connections in a structured and interactive way.

What It Does

LinkSeek is an agentic graph analysis app that enables users to:

  • Query large-scale event graphs using natural language.
  • Dynamically visualize relationships between events, organizations, and locations.
  • Extract meaningful insights using graph traversal and AI-driven reasoning.
  • Identify patterns and trends in historical events.

How It Was Built

This project was built solo, integrating several technologies:

  • Database: ArangoDB for efficient graph storage and querying.
  • Backend & AI: Jupyter Notebooks, Flask, and LangChain for processing natural language queries.
  • Visualization: CosmoGraph, an interactive WebGL-powered graph renderer, for fluid, large-scale graph visualization.
  • UI & Deployment: Gradio (Miko theme by NoCrypt) for an intuitive web interface.
  • Visuals & Branding: Designed with Freepik assets, hosted on Imgur and IBB.

Challenges Faced

  • Data Processing: Structuring GDELT data efficiently for graph-based queries.
  • LLM Accuracy: Reducing hallucinations in AI-generated graph queries.
  • Performance Optimization: Ensuring fast retrieval of complex graph relationships.
  • UI Design: Integrating Gradio's Miko theme while maintaining functionality.
  • Graph Rendering: Optimizing CosmoGraph to handle large-scale event visualizations smoothly.

Accomplishments

  • Successfully integrated graph-based reasoning with natural language queries.
  • Built an intuitive, interactive UI for exploring large-scale event data.
  • Optimized graph queries for fast and accurate insights.
  • Integrated Cosmograph for high-performance event graph visualization.
  • Designed branding and UI visuals using Freepik and hosted images.

Lessons Learned

  • Graph databases are highly effective for event relationship analysis.
  • Optimized indexing and caching greatly improve query performance.
  • LLMs require structured prompts to generate reliable queries.
  • Aesthetic UI design enhances user engagement and usability.
  • CosmoGraph is a powerful tool for rendering large, interactive graphs efficiently.

Next Steps for LinkSeek

  • Integrate real-time GDELT updates for live event tracking.
  • Improve AI models for better natural language understanding.
  • Enhance CosmoGraph visualizations for deeper event insights.
  • Expand query capabilities to support more complex analysis.

Credits

  • Database & AI: ArangoDB, LangChain, Flask
  • Visualization: Cosmograph
  • UI Design: Gradio (Miko theme by NoCrypt)
  • Visual Assets: Freepik, hosted on Imgur & IBB
  • Dataset: GDELT
  • CodePen Home menu : with awesome hover from Swarup Kumar Kuila
  • Video Submission: Arranged on FlexClip
  • Video background sound: Inspiring Corporate Vibes by Nancy_Sinclair -- https://freesound.org/s/754391/ -- License: Creative Commons 0

Usage Rights

LinkSeek is an open-source project under the MIT License. Contributions and feedback are welcome!

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