app.py

import gradio as gr
import os
import requests

# Set your Groq API key
GROQ_API_KEY = os.getenv("GROQ_API_KEY")  # Make sure this is set in Hugging Face Spaces or locally

# Prompt template
def build_prompt(term):
    return f"""
You are EngGloss, an expert AI tutor who explains complex engineering concepts so that absolute beginners can understand them.

Given a single technical engineering term, respond with a structured explanation in the following format:

🔍 Term: {term}

📘 Simple Explanation: Provide a short, beginner-friendly definition using simple language. Avoid technical jargon or complex descriptions.

🧠 Real-World Analogy: Give a relatable analogy using everyday objects or situations to help users intuitively grasp the concept.

📐 Typical Formula: If the term involves a common or standard formula, provide it and briefly explain each variable. If no formula is commonly associated with the term, say so.

🏗️ Engineering Applications: List 2–3 engineering disciplines (e.g., civil, mechanical, electrical) where this term is commonly used.

Make sure your response is clear, concise, and useful for students or beginners in engineering.
"""

# Groq API call
def explain_term(term):
    url = "https://api.groq.com/openai/v1/chat/completions"
    headers = {
        "Authorization": f"Bearer {GROQ_API_KEY}",
        "Content-Type": "application/json"
    }
    payload = {
        "model": "llama3-70b-8192",
        "messages": [
            {"role": "user", "content": build_prompt(term)}
        ],
        "temperature": 0.7
    }

    response = requests.post(url, headers=headers, json=payload)

    if response.status_code == 200:
        result = response.json()
        return result['choices'][0]['message']['content']
    else:
        return f"Error: {response.status_code} - {response.text}"

# Gradio UI
with gr.Blocks() as demo:
    gr.Markdown("## 🤖 EngGloss — Your AI Engineering Glossary Tutor")
    gr.Markdown("Enter an engineering term to get a beginner-friendly explanation:")

    with gr.Row():
        term_input = gr.Textbox(label="Engineering Term", placeholder="e.g., Torque")
        output = gr.Markdown()

    submit_btn = gr.Button("Explain")

    submit_btn.click(fn=explain_term, inputs=term_input, outputs=output)

# Launch
if __name__ == "__main__":
    demo.launch()