Hi everyone!
I’m a student developer. Recently, I created Explore Singapore, a RAG-based search engine that scrapes about 20,000 pages of Singaporean government acts and laws.
I recently posted the MVP and received some tough but essential feedback about hallucinations and query depth. I took that feedback, focused on improvements, and just released Version 2.
Here is how I upgraded the system from a basic RAG to a production-grade one.
The Design & UI I aimed to avoid a dull government website.
Design: Heavily inspired by Apple’s minimalist style.
Tech: Custom frontend interacting with a Python backend.
The V2 Engineering Overhaul
The community challenged me on three main points. Here’s how I addressed them:
1. The "Personality" Fix Issue: I use a "Triple Failover" system with three models as backup. When the main model failed, the backups sounded entirely different.
The Solution: I added Dynamic System Instructions. Now, if the backend switches to Model B, it uses a specific prompt designed for Model B’s features, making it mimic the structure and tone of the primary model. The user never notices the change.
2. The "Deep Search" Fix Issue: A simple semantic search for "Starting a business" misses related laws like "Tax" or "Labor" acts.
The Solution: I implemented Multi-Query Retrieval (MQR). An LLM now intercepts your query. It breaks it down into sub-intents (e.g., “Business Registration,” “Corporate Tax,” “Employment Rules”). It searches for all of them at the same time and combines the results.
Result: Much richer, context-aware answers.
3. The "Hallucination" Fix Issue: Garbage In, Garbage Out. If FAISS retrieves a bad document, the LLM produces inaccurate information.
The Solution: I added a Cross-Encoder Re-Ranking layer.
Step 1: FAISS grabs the top 10 results.
Step 2: A specialized Cross-Encoder model evaluates them for relevance.
Step 3: Irrelevant parts are removed before they reach the Chat LLM.
*
The Tech Stack *
Embeddings: BGE-M3 (Running locally)
Vector DB: FAISS
Backend: Python + Custom Triple-Model Failover
Logic: Multi-Query + Re-Ranking (New in V2)
Try it out
I am still learning. I’d love to hear your thoughts on the new logic.
Live Demo: https://adityaprasad-sudo.github.io/Explore-Singapore/
GitHub Repo: https://github.com/adityaprasad-sudo/Explore-Singapore
Feedback, especially on the failover speed, is welcome!
