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EcoImpact AI

Overview

EcoImpact AI is a sustainability-focused AI system that provides eco-friendly solutions through intelligent agents. It consists of a FastAPI backend for AI processing and a Next.js 15 frontend.

Tech Stack

  • Backend: FastAPI, Python, Redis Queue (RQ), OpenAI API
  • Frontend: Next.js 15, TypeScript, Material-UI (MUI)
  • Database & Caching: Redis for task management

Features

  • AI-powered agents for sustainability guidance
  • Redis Queue for background task handling
  • Next.js 15 frontend with Material-UI
  • Dark Mode UI with chat-based interaction
  • API with CORS support for smooth communication

Getting Started

Backend Setup (FastAPI + Redis + RQ)

# Clone the repository
git clone https://github.com/yourrepo/EcoImpact-AI.git
cd EcoImpact-AI

# Create a virtual environment
python3 -m venv venv
source venv/bin/activate  # macOS/Linux
venv\Scripts\activate    # Windows

# Install dependencies
pip install -r requirements.txt

# Start Redis
redis-server

# Start the backend server
uvicorn backend.api.main:app --reload

Frontend Setup (Next.js 15 + MUI)

# Move to frontend directory
cd frontend

# Install dependencies
yarn install  # or npm install

# Start the frontend server
yarn dev  # or npm run dev

AI Agents

  • GeneralAgent: Handles general sustainability questions
  • TransportAgent: Provides eco-friendly transport advice
  • EnergyAgent: Suggests energy-efficient practices
  • FoodAgent: Recommends sustainable food choices

API Endpoints

  • GET / Root API endpoint
  • GET /assign-task/ Assigns a task to an agent
  • GET /job-result/ Fetches task results
  • DELETE /reset-memory/ Clears user memory

API Usage with cURL

1) Assign a Task to an AI Agent

curl -X GET "http://127.0.0.1:8000/assign-task/" \
     -H "Content-Type: application/json" \
     --data-urlencode "user_id=user_123" \
     --data-urlencode "agent_name=transport_agent" \
     --data-urlencode "user_input=How can I reduce my carbon footprint?"

Response Example:

{
  "status": "job_id_123456789"
}

2) Fetch Task Result

curl -X GET "http://127.0.0.1:8000/job-result/" \
     -H "Content-Type: application/json" \
     --data-urlencode "job_id=job_id_123456789"

Response Example:

{
  "status": "completed",
  "result": "Use public transport, carpool, or switch to an electric vehicle."
}

3) Reset AI Memory

curl -X DELETE "http://127.0.0.1:8000/reset-memory/" \
     -H "Content-Type: application/json" \
     --data-urlencode "user_id=user_123"

Response Example:

{
  "message": "User memory reset successfully."
}