Eco-Match (Climate-Tech Career Counsellor Platform)

Features

• ** AI-Powered**: Uses Google Gemini Pro for intelligent responses
• ** Climate-Tech Expertise**: Specialized knowledge across 6 key sectors:
  • Buildings (heat pumps, smart buildings, sustainable materials)
  • Manufacturing (green hydrogen, industrial electrification)
  • Transportation (EVs, hydrogen fuel cells, sustainable aviation)
  • Food, Agriculture & Nature (methane reduction, regenerative farming)
  • Electricity (renewables, energy storage, grid modernization)
  • GHG Removal (direct air capture, carbon sequestration)
• ** Smart Context Retrieval (RAG)**: Automatically injects relevant climate-tech context based on your queries
• ** Keyword Filtering**: Detects and emphasizes climate-tech topics in conversations
• ** Interactive UI**: Clean, responsive chat interface with typing indicators and suggestions

Tech Stack

• Frontend: HTML, CSS, JavaScript (Vanilla)
• Backend: Node.js + Express
• AI: Google Gemini API
• Data: JSON-based knowledge base with comprehensive climate-tech taxonomy

Prerequisites

• Node.js 18.x or higher
• A free Google Gemini API key (Get one here)

Installation

1. Clone or download this repository

2. Install dependencies

   npm install
   

3. Get your free Gemini API key

   • Visit Google AI Studio
   • Sign in with your Google account
   • Click "Create API Key"
   • Copy your API key

4. Configure environment variables

   • Open the .env file
   • Replace your_api_key_here with your actual Gemini API key:

   GEMINI_API_KEY=your_actual_api_key_here
   PORT=3000
   

Usage

1. Open your browser

   • Navigate to https://eco-match-treehacks-2026.vercel.app/

2. Start chatting!

   • Try asking about:
     • "What are heat pumps and how do they work?"
     • "How can we decarbonize transportation?"
     • "Tell me about direct air capture"
     • "What are climate-tech moonshots?"

Project Structure

.
├── index.html              # Main chat interface
├── styles.css              # UI styling (climate-themed)
├── app.js                  # Frontend JavaScript
├── server.js               # Express backend + Gemini integration
├── climate-knowledge.json  # Climate-tech taxonomy database
├── package.json            # Node dependencies
├── .env                    # Environment variables (API key)
├── .gitignore              # Git ignore rules
└── README.md               # This file

How It Works

1. System Prompt Configuration

The chatbot is configured with a specialized system prompt that establishes it as a climate-tech expert with knowledge across all 6 sectors.

2. Keyword Extraction

When you send a message, the backend analyzes your query to extract climate-tech keywords (e.g., "heat pumps", "carbon capture", "solar", etc.).

3. Context Retrieval (RAG)

Based on extracted keywords, the system retrieves relevant information from the climate knowledge base:

• Sector descriptions
• Key technologies
• Innovation imperatives
• Moonshot projects

4. Enhanced Prompt

The retrieved context is injected into the prompt sent to Gemini, ensuring responses are grounded in climate-tech knowledge.

5. Intelligent Response

Gemini generates a comprehensive response using both its base knowledge and the injected climate-tech context.

Example Queries

• "What are the main technologies for decarbonizing buildings?"
• "How does green hydrogen work and where can it be used?"
• "What's the difference between DAC and BECCS?"
• "Tell me about regenerative agriculture"
• "What are the challenges with electric vehicles?"
• "How can we reduce methane emissions from livestock?"
• "What innovations are needed for sustainable aviation?"
• "Explain grid-scale battery storage"

API Endpoints

POST /api/chat

Send a message to the chatbot.

Request:

{
  "message": "What are heat pumps?"
}

Response:

{
  "response": "Heat pumps are...",
  "metadata": {
    "keywords": ["heat_pumps", "buildings"],
    "sectorsReferenced": ["Buildings"]
  }
}

GET /api/health

Check server health status.

Response:

{
  "status": "ok",
  "message": "Climate-Tech Chatbot API is running",
  "sectorsLoaded": 6
}

Troubleshooting

"Invalid API key" error

• Make sure you've added your Gemini API key to the .env file
• Verify the key is correct (no extra spaces or quotes)
• Ensure you've created the API key at Google AI Studio

"API quota exceeded" error

• The free Gemini API has rate limits
• Wait a few minutes and try again
• Consider upgrading to a paid plan if needed

Server won't start

• Make sure Node.js 18+ is installed: node --version
• Delete node_modules and run npm install again
• Check if port 3000 is available (or change PORT in .env)

Customization

Adding More Climate Data

Edit climate-knowledge.json to add:

• New sectors
• Additional technologies
• More keywords for better matching
• Custom imperatives or moonshots

Changing the AI Model

In server.js, line 17:

const model = genAI.getGenerativeModel({ model: 'gemini-pro' });

You can change to other Gemini models if needed.

Styling

Edit styles.css to customize:

• Colors and theme
• Layout and spacing
• Responsive breakpoints

Credits

• Climate Data: Climate Tech Map by Breakthrough Energy, Stanford, and McKinsey
• AI: Google Gemini API
• Built for: TreeHacks 2026

License

ISC

Support

For issues or questions, please check:

1. This README
2. Server console logs
3. Browser console (F12)

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