Explore-Singapore delivers precise information about Singapore's legal system, policies, and historical context through a sophisticated RAG intelligence engine. With a unique triple-AI backend and over 33,000 curated documents, it ensures accurate, relevant answers while minimizing the risk of misinformation.
Explore Singapore - Legal, Historical, and Infrastructural Knowledge Engine
The Explore Singapore project is an advanced intelligence engine designed to provide accurate and relevant information regarding Singapore's legal framework, policies, historical events, and critical infrastructure. This system employs a sophisticated Retrieval-Augmented Generation (RAG) approach to mitigate inaccuracies often found in other language models, ensuring that users receive data grounded in factual reality. Leveraging a comprehensive dataset comprising over 33,000 pages of curated documents, this platform aims to enhance the user's understanding of Singaporean law and governance.
Key Features
Triple-AI Failover Backend
To guarantee reliability, the system is powered by a robust chain of command for language model inference consisting of:
- Primary: Google Gemini 2.0 Flash
- Secondary: Llama 3.3 70B via OpenRouter
- Tertiary: Llama 3.3 70B via Groq
This architecture provides a 99.9% uptime, making it ideal for heavy traffic scenarios.
Interactive "Liquid-Glass" User Interface
The user interface utilizes modern web design principles, featuring a custom-built React component with:
- Glassmorphism: Aesthetic backdrop blur for a sleek appearance.
- Smooth Animation: Spring physics for fluid interactions.
- Minimalist Design: Emphasis on clarity with SVG icons and elegant typography.
Local Embedding Inference
The platform prioritizes performance and privacy by executing the embedding model locally, avoiding external API calls that could introduce latency and additional costs.
System Architecture
The system architecture employs a high-performance RAG pipeline optimized for low-resource environments, comprising the following stages:
- Ingestion: Processing of over 33,000 pages of legal and historical documents from Singapore.
- Vectorization: Utilizing
BGE-M3to produce 1024-dimensional semantic embeddings. - Retrieval: Implementation of FAISS (Facebook AI Similarity Search) to achieve millisecond-latency vector lookups.
- Generation: A failover logic that ensures continuous uptime and performance.
Tech Stack
| Component | Technology | Description |
|---|---|---|
| Frontend | React, Framer Motion | Interactive "Ask AI" widget. |
| Backend | Flask, Gunicorn | REST API managing RAG logic. |
| Vector DB | FAISS (CPU) | Local, high-speed similarity search. |
| Embeddings | Sentence-Transformers | BGE-M3 (On-premise execution). |
| LLMs | Gemini 2.5 flash, Llama 3.3 | Text generation and synthesis capabilities. |
| Deployment | Hugging Face Spaces | Cloud hosting using Docker technology. |
Explore Singapore is not just a knowledge repository; it is a comprehensive tool designed to facilitate a greater understanding of Singapore's legal landscape, its policies, and the history that shapes this vibrant nation.
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