LLM Identifier & Wiki

A web application to identify unknown LLMs by comparing their responses to a library of known LLMs. The web application also contains a built-in wiki with curated LLM info. This repository contains production services, data collection tooling, experimental scripts, and a frontend for interacting with the classifier and wiki.

Deployed website link: https://llmdetective.ca/

White paper: ai-identities_summer2025_white_paper.pdf

Check out the demo video below for a walkthrough of our application's main features!

Demo.of.the.Main.Workflow.mp4

Table of contents

1. Repository structure
2. Quick start
3. Where to find more detail

Repository structure

├── classifier_service/       # Production classification backend
├── frontend/                 # Web application frontend files
├── response_classifier/      # Classifier methods: data, scripts, results
├── xwiki/                    
├── ai-identities_summer2025_white_paper.pdf  # White paper detailing the project and final web application              
└── README.md                 # (this file)

Folder	Description
classifier_service/	Production-ready classification service code. This is the core backend service that takes in responses and returns predicted LLM matches.
frontend/	Frontend files for the deployed web application (includes home page, LLM fingerprinting tool, and the LLM wiki)
response_classifier/	Data collection, analysis scripts, model experiments, configs, and results for classifier methods research.

Each of the folders above should contain its own README.md with more detailed explanation and instructions.

Quick start

How to clone the repository

git clone [email protected]:CSC392-CSC492-Building-AI-ML-systems/ai-identities.git
cd ai-identities

Where to find more detail

Each major folder should contain a README.md with detailed explanations of its content. Start with:

• classifier_service/README.md — classifier service used by the web application
• frontend/README.md — web application frontend
• response_classifier/README.md — dataset, data collection scripts, classifier method experiment files, and config files