title	EnergyMind AI
emoji	⚡
colorFrom	blue
colorTo	indigo
sdk	docker
pinned	false

Autonomous Energy Researcher Agent

A full-stack AI agent application that researches energy topics using CrewAI, powered by FastAPI (Backend) and Streamlit (Frontend).

Prerequisites

• Python 3.10+
• Groq API Key (for LLM)
• Tavily API Key (for Search)

Installation & Setup

1. Clone the Repository

   git clone https://github.com/pranjal1712/energymind-ai-agents.git
   cd energymind-ai-agents

2. Create Virtual Environment It's recommended to use a virtual environment to manage dependencies.

   # Windows
   python -m venv venv
   .\venv\Scripts\activate
   
   # Mac/Linux
   python3 -m venv venv
   source venv/bin/activate

3. Install Dependencies

   pip install -r requirements.txt

4. Environment Variables This project requires API keys for LLM and Search.

   • Copy the example environment file:

     # Windows (PowerShell)
     cp .env .env.example
     
     # Mac/Linux
     cp .env.example .env

   • Open .env and add your API keys:

     GROQ_API_KEY=your_key_here
     TAVILY_API_KEY=your_key_here

Running the Application

You need to run the Backend and Frontend in two separate terminals.

1. Start the Backend (FastAPI)

Open a new terminal, activate the venv, and run:

uvicorn backend.main:app --reload

The API will start at http://localhost:8000.

2. Start the Frontend (Streamlit)

Open another terminal, activate the venv, and run:

streamlit run frontend/app.py

The UI will automatically open in your browser at http://localhost:8501.

Features

• Project Structure: Clean separation of Backend and Frontend.
• Autonomous Agents: Uses CrewAI with Research, Analyst, and Writer agents.
• Persistence: Saves research results as text files in backend/knowledge_base/.
• API: FastAPI endpoints for triggering research and retrieving history.
• UI: Simple Streamlit interface.

Tech Stack

• Backend: FastAPI, Langchain, Pydantic
• Frontend: Streamlit
• Tools: Tavily (Search), Python-Slugify