Androcles
Androcles is our inhouse Prompt Classification Model, used to classify user prompts into different categories to dynamically change the functionality based on the context of the request. It's a simple text classification model finetuned on a mix of synthetic & open source data across 21 labels
No Brave Browser/Leo user data was used to train this model - even if we wanted to, we don't have it
Labels
| Label | Short Description |
|---|---|
| Brave | The user is asking about Brave products — Brave Browser, Brave Search, Brave Rewards |
| Browser | The user wants Leo to take actions in the browser — clicking, filling forms, navigating pages |
| Choice | The user is deciding between two or more specific options and wants help choosing |
| Coding | Anything related to coding — writing, reading, understanding, explaining, or running code in any language |
| Data Analysis | The user has data they want analysed, visualised, or interpreted — CSV, JSON, a table, or raw numbers |
| Diagrams | The user wants a diagram, flowchart, chart, or visual representation of a system or process |
| Fact Checking | The user is asking whether a claim, statement, or piece of information is true or false |
| Finance | The user is asking about money — currrency exchange/stock prices etc |
| Image Generation | Generating an image — the user is explicitly asking for an image to be created or produced |
| Math / Calculations | Anything involving numbers, arithmetic, algebra, statistics, or mathematical reasoning |
| Multilingualism | The user is writing in or asking for a response in a non-English language |
| News | The user is asking about current events, recent news, or what's happening in the world |
| Recommendation | The user is asking for a recommendation — a product, service, tool, or option suited to their needs |
| Sports | The user is asking about sports — scores, fixtures, standings, results, or sports news |
| Structured Writing | The user wants help writing something structured and polished — a cover letter, essay, email, report, blog post etc |
| Summarisation | The user wants a summary of something — an article, video, document, or piece of text |
| Thinking | The user wants Leo to think through something carefully and methodically — a complex problem, a multi-step question, or a nuanced topic |
| Time-critical | The request is urgent or time-sensitive — the user needs a fast answer, not a thorough one |
| Translation | Translating text from one language to another |
| Travel Planning | The user is planning a trip — flights, hotels, itineraries, destinations, things to do |
| Weather | The user is asking about the weather — current conditions, forecasts, or climate for a location |
Training
Androcles 2 was trained using a mix of bravesoftware/diverse-llm-prompts-34k + labelled data from LMSYS/lmsys-chat-1m
The scripts for training the model & generating the initial dataset can be found here
How We Use It
We use Androcles in a couple of different ways:
As a first step in our AI Gateway Server powering Leo, classifying prompts into categories with the aim of dynamically changing available tools/instructions depending on what the user asks for
As a 'primary category' labeller for our privacy-preserving Leo Analytics server
We host it using Nvidia's Triton Inference Server to serve it with low-latency at scale, but we've also used KServe in the past
Caveats
This model was not trained to be perfect and will make mistakes in classification, the aim was to catch some low-hanging fruit semantically to improve the user experience