import streamlit as st
import pandas as pd
import requests
from io import BytesIO
import os

# --- CONFIGURATION ---
EXCEL_CSV_URL = "https://docs.google.com/spreadsheets/d/1b_gBz-_TZZNJLIM5sYyYJQfBVNua7dFf/export?format=csv"
GROQ_API_KEY = os.getenv("GROQ_API_KEY")  # Ensure this is set in your environment
GROQ_URL = "https://api.groq.com/openai/v1/chat/completions"
LLAMA3_MODEL = "llama3-8b-8192"

# --- FUNCTIONS ---

def load_excel_data():
    try:
        response = requests.get(EXCEL_CSV_URL)
        response.raise_for_status()
        df = pd.read_csv(BytesIO(response.content))
        return df
    except Exception as e:
        st.error(f"Error loading sheet: {e}")
        return pd.DataFrame()

def search_student(data, roll_number, student_name):
    df = data.copy()
    # Normalize column names
    df.columns = [col.strip().lower().replace(" ", "_") for col in df.columns]
    # Normalize input
    roll_number = roll_number.strip().lower()
    student_name = student_name.strip().lower()
    # Search for matching row
    result = df[
        (df['roll_number'].astype(str).str.lower() == roll_number) &
        (df['student_name'].astype(str).str.lower() == student_name)
    ]
    return result

def generate_summary_from_data(student_row):
    content = student_row.to_dict(orient="records")[0]
    prompt = (
        f"Generate a detailed student result summary in the following format:\n\n"
        f"Student Name: {content.get('student_name', '')}\n"
        f"Roll Number: {content.get('roll_number', '')}\n"
        f"Class: {content.get('class', '')}\n"
        f"Subjects and Marks:\n"
    )
    # Add subjects and marks
    for key, value in content.items():
        if key not in ['student_name', 'roll_number', 'class']:
            prompt += f"{key.replace('_', ' ').title()}: {value}\n"
    prompt += "\nInclude total marks, percentage, and a performance remark."

    headers = {
        "Authorization": f"Bearer {GROQ_API_KEY}",
        "Content-Type": "application/json"
    }
    data = {
        "model": LLAMA3_MODEL,
        "messages": [
            {"role": "system", "content": "You are a student result generator for a school."},
            {"role": "user", "content": prompt}
        ]
    }

    response = requests.post(GROQ_URL, headers=headers, json=data)
    response.raise_for_status()
    return response.json()["choices"][0]["message"]["content"]

# --- UI ---

def main():
    st.set_page_config("🎓 Student Result Lookup", layout="centered")
    st.title("🎓 Student Result Generator with AI")

    st.markdown("Enter your **Roll Number** and **Student Name** to generate your result.")

    roll_number = st.text_input("Roll Number", placeholder="e.g., k0000")
    student_name = st.text_input("Student Name", placeholder="e.g., Ahmed Raza")

    if st.button("Generate Result"):
        with st.spinner("📥 Loading data and generating result..."):
            data = load_excel_data()
            if data.empty:
                return
            try:
                result = search_student(data, roll_number, student_name)
                if not result.empty:
                    st.success("✅ Student found. Generating summary...")
                    summary = generate_summary_from_data(result)
                    st.markdown("### 📝 Result Summary:")
                    st.markdown(summary)
                else:
                    st.warning("❌ No student found with that roll number and name.")
            except Exception as e:
                st.error(f"❌ Error: {e}")

if __name__ == "__main__":
    main()