I Built an AI Pet Symptom Checker — Here's What the Data Taught Me About Pet Owner Anxiety

Last year I shipped a side project: an AI-powered pet symptom checker. I expected to learn about NLP. What I actually learned was about human psychology . Here's the breakdown — including the code patterns that made it actually useful. The Problem Pet owners Google symptoms at 2am in a panic. They get SEO-optimized horror stories. They either rush to an expensive ER or convince themselves everything is fine when it isn't. The signal-to-noise ratio is terrible. I wanted to fix that. The Architecture The core is a simple pipeline: import openai from dataclasses import dataclass from enum import Enum class UrgencyLevel ( Enum ): MONITOR = " monitor " CALL_VET = " call_vet " EMERGENCY = " emergency " @dataclass class SymptomResult : urgency : UrgencyLevel explanation : str next_steps : list [ str ] confidence : float def analyze_pet_symptoms ( symptoms : str , species : str , age_years : float , weight_kg : float ) -> SymptomResult : prompt = f """ You are a veterinary triage assistant. Pa