Project Info

PETSOS

This project did not submit a demo video on Devpost.

Inspiration

This project was inspired by my family friend's loss of their dog during a critical moment of crisis. It shed light on an overlooked issue: emergency pet health service. As a pet owner, it terrifies me that there is no 911 for our loved pets. So with the power of AI - I took on the challenge.

What it does

PET911 is a voice-activated emergency assistant that guides pet owners through life-threatening situations — completely hands-free. It simulates a real 911-style call for pets and responds with calm, intelligent, and timely support. Here's what it does: 🗣️ Understands your voice in real-time Users can call a real phone number and speak naturally. PET911 uses voice streaming through Vapi to transcribe speech instantly and maintain a fluid, multi-turn conversation. 🤖 Provides life-saving guidance using AI Powered by Claude, the assistant triages emergencies by asking crucial questions and delivering context-specific, step-by-step instructions (e.g., performing the Heimlich maneuver for a choking dog based on its breed and weight). 🧠 Remembers what you said The assistant uses memory from the conversation so it doesn’t repeat itself or forget details like the pet’s condition or size — enabling natural, human-like dialogue even in high-stress moments. 🌐 Finds the closest emergency vet clinic PET911 uses your ZIP code or live coordinates to identify and link you to the closest open emergency clinic—ensuring fast, location-aware care when every second counts. 📍 Sends an SMS with directions PET911 identifies a nearby emergency clinic and sends a text message with a direct link to the location. This allows the user to begin navigation immediately — skipping the stress of searching online or fumbling with maps during a crisis. 🔄 Transfers to a live vet If needed, PET911 offers to transfer the call to a pre-set backup assistant, simulating the experience of speaking with a real vet receptionist in the area — for needed escalation. ❤️ Offers emotional support The AI is designed to be calm, empathetic, and reassuring — because pet emergencies are overwhelming, and users need to feel safe and heard.

How we built it

PET911 runs on a modular multi-agent system built with a Flask backend. A voice interface powered by Vapi captures real-time input, which is routed through specialized agents: a Triage Agent for rapid emergency assessment, a Memory Agent for contextual continuity, and a Decision Agent to determine next steps. Claude serves as the core reasoning engine. For location support, we integrated OpenStreetMap, and emergency routing is handled via SMS through Textbelt.

Challenges we ran into

We hit roadblocks integrating Fetch.ai’s Python SDK due to package conflicts, which led us to rethink how we handled real-time vet discovery. Vapi's real-time voice streaming also came with unexpected 404 webhook issues and delayed responses, requiring deep debugging. On top of that, prompting Claude for step-by-step, non-overwhelming instructions demanded careful prompt engineering to simulate a calm, conversational emergency assistant.

Accomplishments we're proud of

Built a fully functional voice AI emergency system from scratch using Vapi and Claude, with natural, multi-turn memory and contextual awareness. Integrated a simulated agent ecosystem combining triage, decision-making, and location support under emergency pressure. Engineered real-time responses that adapt to user input instead of overwhelming them—just like a real 911 operator would. Successfully routed emergency info via SMS, with geolocation-based vet directions and calming follow-ups. Debugged complex streaming issues and webhooks under time pressure and got everything running seamlessly across tools.

What we learned

Building PET911 taught me how to design for urgency, empathy, and clarity under pressure. I deepened my skills in real-time voice interaction, multi-agent system design, and external API integration. I also learned how to troubleshoot complex streaming and webhook errors, all while keeping the user experience as the top priority—especially in life-or-death scenarios.

🐾 PET911 - AI-Powered Pet Emergency Assistant

A voice-activated AI assistant for pet emergencies with real-time SMS notifications and vet locator services.

🚀 Features

Core Functionality

Voice-Activated Emergency Response - Natural conversation with pet owners during emergencies
Real-Time SMS Notifications - Automatic vet locator links sent via SMS when calls start
Intelligent Triage System - Step-by-step first-aid guidance for common pet emergencies
Live Vet Transfer - Seamless transfer to emergency veterinarians when needed
Bilingual Support - English and Spanish language support
Vet Locator Service - Web-based emergency clinic finder with directions

Technical Features

Real-Time Decision Logic - Dynamic webhook processing with intelligent event routing
Robust Phone Number Detection - Recursive payload analysis for reliable SMS delivery
Quota Management - Smart SMS limiting to prevent API abuse
Error Handling - Graceful fallbacks and comprehensive logging
Memory-Free Design - Consistent, reliable responses every time

🛠️ Tech Stack

Backend: Flask (Python)
Voice Platform: Vapi.ai
LLM: Anthropic Claude 3 Haiku
SMS Service: Textbelt API
Geolocation: OpenStreetMap Nominatim API
Voice Synthesis: ElevenLabs
Speech Recognition: Deepgram Nova-2

📋 Prerequisites

Python 3.8+
ngrok (for webhook tunneling)
Vapi.ai account
Anthropic API key
Textbelt API key
ElevenLabs API key

🚀 Quick Start

1. Clone the Repository

git clone https://github.com/yourusername/pet911.git
cd pet911

2. Install Dependencies

pip install -r requirements.txt

3. Environment Setup

Create a .env file in the root directory:

ANTHROPIC_API_KEY=your_anthropic_key_here
TEXTBELT_API_KEY=your_textbelt_key_here
ELEVENLABS_API_KEY=your_elevenlabs_key_here

4. Start ngrok Tunnel

ngrok http 5000

5. Configure Vapi Assistant

Go to Vapi.ai Dashboard
Create a new assistant
Set the webhook URL to your ngrok URL + /vapi-webhook
Configure voice settings (ElevenLabs recommended)
Set up phone number routing

6. Run the Application

python app.py

📁 Project Structure

petSOS/
├── agents/
│   ├── __init__.py
│   ├── llm_agent.py          # Claude LLM integration
│   └── triage_agent.py       # Emergency triage logic
├── vet_locator/
│   ├── main_agent.py         # Vet locator service
│   ├── sms_service.py        # SMS integration
│   └── templates/
│       └── index.html        # Vet locator web interface
├── app.py                    # Main Flask application
├── requirements.txt          # Python dependencies
├── test_sms.py              # SMS testing utility
└── README.md                # This file

🔧 Configuration

SMS Settings

Target Numbers: Configure in app.py line 264
SMS Quota: Adjust MAX_SMS_PER_SESSION in app.py line 30
Vet Locator URL: Update VET_LOCATOR_URL in app.py line 28

Emergency Response

Transfer Number: Set in Vapi assistant configuration
First Aid Protocols: Customize in agents/llm_agent.py
Language Support: Configure in system prompts

🧪 Testing

Test SMS Functionality

python test_sms.py

Test Vet Locator

Start the Flask server
Visit http://localhost:5000/vet-locator
Enter a location to find nearby clinics

Test Voice Assistant

Call your configured Vapi phone number
Describe a pet emergency
Verify SMS is sent automatically
Test vet transfer functionality

📊 API Endpoints

POST /vapi-webhook/chat/completions - LLM chat completions
POST /vapi-webhook - Vapi event webhooks
GET /vet-locator - Vet locator web interface
POST /vet-locator/api/clinics - Clinic search API
GET /vet-locator/api/health - Health check

🔒 Security Considerations

API keys stored in environment variables
SMS quota limiting to prevent abuse
Input validation on all endpoints
Error handling without sensitive data exposure

🤝 Contributing

Fork the repository
Create a feature branch (git checkout -b feature/amazing-feature)
Commit your changes (git commit -m 'Add amazing feature')
Push to the branch (git push origin feature/amazing-feature)
Open a Pull Request

📝 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

Vapi.ai for voice platform infrastructure
Anthropic for Claude LLM capabilities
OpenStreetMap for geolocation services
Textbelt for SMS delivery
ElevenLabs for voice synthesis

📞 Support

For support, email support@pet911.com or create an issue in this repository.

Built with ❤️ for pet safety and emergency response

Analysis

Compare with all teams

View

Metric

ashleyvarghese
1

Figures cover GitHub contributors during the hackathon window. A co-authored commit counts in full for each author, so per-member totals add up to more than the whole-team figures.

Technology

Found in codeClaimed only

AnthropicIn code
FlaskIn code
HTMLIn code
PythonIn code
JavaScriptClaimed

4 of 5 appear in the indexed code. 1 claimed on Devpost could not be matched to code, which may simply mean the tool leaves no trace in the repository.

AI coding agents

No AI coding agent signals were found in this repository.

Detected from committed agent config files and commit authorship. Absence of a signal is not proof an agent was unused.

Codebase size

Source size

53 KB

Source files

Counts recognized source files only; vendored directories, binaries and lockfiles are excluded, so this is smaller than the repository on disk.