☀️ LocEnergy 2.0

A FastAPI-powered web application that estimates solar energy potential and installation costs for a given location using Google’s Solar and Places APIs, and integrates Gemini AI for smart insights.

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🚀 Features

• 🌍 Get solar energy data by providing latitude and longitude
• 🏢 Retrieve nearby place information using Google Places API
• 🤖 Generate AI-based cost estimates using Gemini Pro (Google’s LLM)
• ⚙️ FastAPI backend with RESTful routes
• 🐳 Dockerized for easy deployment
• ☁️ Deployed on Google Cloud Run with CI/CD via Cloud Build

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🧰 Tech Stack

Layer	Technology
Backend	Python, FastAPI
AI	Gemini Pro (via REST API)
External APIs	Google Solar API, Places API
Deployment	Docker, Cloud Build, Cloud Run
Env Mgmt	python-dotenv
Frontend	HTML + Tailwind CSS (served via StaticFiles)

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📦 API Endpoints

GET /predict

Fetch solar building insights for a location.

Query Parameters:

• lat: Latitude (float)
• lng: Longitude (float)

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GET /place_info

Get nearby restaurants (or places) for the specified location.

Query Parameters:

• lat: Latitude (float)
• lng: Longitude (float)

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GET /get_gemini_suggest

Use Gemini AI to generate insights based on solar data and location.

Query Parameters:

• items: Raw JSON string from the Solar API
• lat: Latitude (float)
• lng: Longitude (float)

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🛠️ Local Development

🔧 Prerequisites

• Python 3.10+
• Docker (optional)
• Google API keys
• Gemini Pro API key

🧪 Setup Steps

1. 🚀 Clone the Repository

git clone https://github.com/adarsh2023calc/LocEnergy2.0.git
cd LocEnergy2.0 

#### 2. 🔐 Install Dependencies & Create `.env` File

Install the required Python dependencies:

```bash
pip install -r requirements.txt```

docker build -t locenergy-app .
docker run -p 8080:8080 locenergy-app


This version ensures:
- Each command block is properly closed.
- Markdown renders cleanly with separated steps.
- You follow standard `README.md` heading practices.

Let me know if you want to add `.env` file example or any Gemini-specific setup tips!