🏢 AltoTech AI-Powered IoT Platform

Welcome to AltoGPT – a generative AI assistant that powers smart building management using real-time sensor data, intelligent insights, and a sleek mobile interface.

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🚀 Features

• Real-time streaming from IAQ, occupancy, and power sensors
• AI-generated summaries, recommendations, and analytics
• Supabase + TimescaleDB integration
• LangChain-powered AI inference pipeline
• Responsive React mobile UI with voice input
• Modular, Dockerized microservices

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📦 Project Structure

ALTOTECH_PROJECT/
├── agents/
│   └── agent_router.py
├── backend/
│   ├── backend_inference_main/      # LangChain AI pipeline
│   ├── rag/                         # Retrieval-Augmented Generation
│   ├── tools/                       # Tools like energy calculator
│   ├── utils/                       # Supabase client helpers
│   ├── main.py                      # FastAPI entrypoint
│   ├── requirements.txt
│   └── Dockerfile
├── consumers/
│   └── combined_consumer.py
├── data/                            # Simulated sensor CSVs
├── producers/
│   └── send_combined_to_rabbitmq.py # Publishes combined IAQ, occupancy, power
├── services/
│   ├── send_combined_to_db.py       # TimescaleDB consumer
│   └── send_combined_to_supabase.py # Supabase real-time updater
├── dashboard/                       # (Optional) Streamlit dashboard
├── frontend/                        # React frontend UI
│   ├── src/
│   └── Dockerfile
├── .env
├── docker-compose.yml
├── .dockerignore
└── README.md

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⚙️ Environment Setup

1. Clone the repo

git clone https://github.com/your-org/altotech-platform.git
cd altotech-platform

2. Create a .env file with:

PG_HOST=localhost
PG_PORT=5432
PG_DATABASE=altotech
PG_USER=postgres
PG_PASSWORD=shreyasha123


SUPABASE_URL=https://wxwmbikghvdoixopbzmr.supabase.co
SUPABASE_KEY=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpc3MiOiJzdXBhYmFzZSIsInJlZiI6Ind4d21iaWtnaHZkb2l4b3Biem1yIiwicm9sZSI6InNlcnZpY2Vfcm9sZSIsImlhdCI6MTc0NDU2OTc0MiwiZXhwIjoyMDYwMTQ1NzQyfQ.nQ7WmOygKGmc7ecPGa60sU6HUgid6mfUdEuV8yOq6Ns


OPENAI_API_KEY=sk-svcacct-vPTeI5m4lr8Omi8Nl--zFO2Dar97AIqPeW3xQH0zYKh80vP-ET34un9o0Fs8xT3BlbkFJuuj6Waf1AhBJnB9YHqmrbEAaXT3yqNyNtmYdmr7mx7leDOzZ-oQTSt6bhEbAA

3. Install backend dependencies

cd backend
pip install -r requirements.txt

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🐳 Run Locally with Docker Compose

docker-compose up --build

This will spin up FastAPI, React, RabbitMQ, and TimescaleDB containers.

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🧪 Testing the System

1. Start sensor simulation (RabbitMQ publisher)

python producers/send_combined_to_rabbitmq.py

2. Start Supabase updater

python services/send_combined_to_supabase.py

3. Start TimescaleDB storage

python services/send_combined_to_db.py

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🌐 Frontend (React UI)

cd frontend
npm install
npm start

Visit: http://localhost:3000

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🔍 REST API Endpoints (FastAPI)

Endpoint	Method	Description
/	GET	Welcome message
/query/	POST	Ask questions to ALTO-GPT (AI inference)
/buildings/	GET	List available buildings
/buildings/{building_id}/status/	GET	Current building sensor overview
/rooms/{room_id}/sensors/{type}/	GET	Get specific sensor data for a room

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🤖 AI Features

• LangChain + GPT-3.5 Turbo powered agent
• Tool calling with sensor summary, power estimation, RAG
• Multi-input tool for direct sensor queries
• Voice input + AI chat interface in frontend
• Summarization with actionable recommendations

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🧪 Testing Instructions

Local Development

• Backend: uvicorn backend.main:app --reload
• Frontend: npm start
• Ensure .env is properly configured for PostgreSQL and Supabase

API Testing Tools

• Use Swagger UI: http://localhost:8000/docs
• Use Postman or curl to test /query/ and /buildings/... routes

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📊 Architecture Diagram

Includes data ingestion, AI inference, and frontend rendering layers.

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🚀 Deployment

• All services are containerized
• Frontend deployed on Vercel: [https://your-vercel-link](#)
• Backend optionally deployed on Render or run locally
• CI/CD with GitHub Actions workflows: test, build, deploy