import gradio as gr
import os
from groq import Groq

# --- API Setup ---
# Hugging Face Spaces reads secrets as Environment Variables
api_key = os.getenv("EngGloss")

# Check for key availability
if not api_key:
    raise ValueError("API Key not found! Please go to your Space 'Settings' > 'Secrets' and create a secret named 'EngGloss' containing your Groq API key.")

client = Groq(api_key=api_key)

# --- The System Prompt ---
system_prompt = """
You are EngGloss, an expert AI engineering tutor. Your goal is to explain technical engineering terms to students and beginners in a way that is structured, strictly factual, yet easy to understand.

When given a term, you must output the response in the following Markdown format:

### 📖 Term: <The Term>

**💡 Simple Explanation:**
<A concise, jargon-free definition (2-3 sentences max). Imagine explaining this to a first-year student.>

**🍎 Real-World Analogy:**
<An analogy using everyday objects (like water, cars, cooking, or sports) to explain the concept.>

**⚙️ Real-World Engineering Applications:**
Provide 3 distinct examples of how this term is applied in different engineering fields. Use this bullet format:
* **[Field Name]:** Specific explanation of how the term is used here. (e.g., "Civil Engineering: Stress and Strain are calculated to ensure bridges can withstand the weight of traffic without collapsing.")
* **[Field Name]:** Specific explanation of how the term is used here.
* **[Field Name]:** Specific explanation of how the term is used here.

**➗ Typical Formula:**
<Display the core formula using LaTeX formatting (e.g., $F=ma$). If no formula exists, write "No standard formula." Brief bullet points explaining the variables.>

Constraint: If the user input is NOT an engineering or scientific term, politely refuse and ask for a valid technical term.
"""

# --- Core Logic Function ---
def explain_term(term):
    if not term.strip():
        return "⚠️ Please enter an engineering term."
    
    try:
        chat_completion = client.chat.completions.create(
            messages=[
                {
                    "role": "system",
                    "content": system_prompt,
                },
                {
                    "role": "user",
                    "content": term,
                }
            ],
            # UPDATED MODEL NAME HERE
            model="llama-3.1-8b-instant", 
            temperature=0.5,
            max_tokens=600,
        )
        return chat_completion.choices[0].message.content

    except Exception as e:
        return f"❌ Error: {str(e)}"

# --- Gradio UI ---
with gr.Blocks(theme=gr.themes.Soft()) as demo:
    gr.Markdown("# ⚙️ EngGloss: AI Engineering Tutor")
    gr.Markdown("Enter an engineering term below to get a structured, beginner-friendly explanation.")
    
    with gr.Row():
        input_text = gr.Textbox(
            label="Enter Engineering Term", 
            placeholder="e.g. Reynolds Number, Torque, Ohm's Law",
            lines=1
        )
    
    submit_btn = gr.Button("Explain Term", variant="primary")
    
    output_markdown = gr.Markdown(label="Explanation")

    # Connect the button to the function
    submit_btn.click(fn=explain_term, inputs=input_text, outputs=output_markdown)
    # Allow pressing "Enter" to submit as well
    input_text.submit(fn=explain_term, inputs=input_text, outputs=output_markdown)

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