import gradio as gr
from datasets import load_dataset, Dataset
from datetime import datetime, date
import os
from PIL import Image, ImageDraw, ImageFont
from huggingface_hub import login
from transformers import pipeline

# Authenticate with Hugging Face
login(token=os.environ["HUGGINGFACE_TOKEN"])

# Constants
SCORES_DATASET = "agents-course/unit4-students-scores"
CERTIFICATES_DATASET = "agents-course/course-certificates-of-excellence"
THRESHOLD_SCORE = 30

# Load text-generation pipeline (FLAN-T5)
qa_pipeline = pipeline("text2text-generation", model="google/flan-t5-base")

# Process question using model
def process_question(question):
    if not question or not isinstance(question, str):
        return "I don't understand the question."
    result = qa_pipeline(question, max_new_tokens=50)
    return result[0]["generated_text"].strip()

# Function to check user score
def check_user_score(username):
    score_data = load_dataset(SCORES_DATASET, split="train", download_mode="force_redownload")
    matches = [row for row in score_data if row["username"] == username]
    return matches[0] if matches else None

# Check if user already has certificate
def has_certificate_entry(username):
    cert_data = load_dataset(CERTIFICATES_DATASET, split="train", download_mode="force_redownload")
    return any(row["username"] == username for row in cert_data)

# Add certificate entry
def add_certificate_entry(username, name, score):
    ds = load_dataset(CERTIFICATES_DATASET, split="train", download_mode="force_redownload")
    filtered_rows = [row for row in ds if row["username"] != username]
    new_entry = {
        "username": username,
        "score": score,
        "timestamp": datetime.now().isoformat()
    }
    filtered_rows.append(new_entry)
    updated_ds = Dataset.from_list(filtered_rows)
    updated_ds.push_to_hub(CERTIFICATES_DATASET)

# Generate certificate
def generate_certificate(name, score):
    certificate_path = os.path.join(os.path.dirname(__file__), "templates", "certificate.png")
    im = Image.open(certificate_path)
    d = ImageDraw.Draw(im)

    name_font = ImageFont.truetype("Quattrocento-Regular.ttf", 100)
    date_font = ImageFont.truetype("Quattrocento-Regular.ttf", 48)

    name = name.title()
    d.text((1000, 740), name, fill="black", anchor="mm", font=name_font)
    d.text((1480, 1170), str(date.today()), fill="black", anchor="mm", font=date_font)

    pdf = im.convert("RGB")
    pdf.save("certificate.pdf")

    return im, "certificate.pdf"

# Handle certificate logic
def handle_certificate(name, profile: gr.OAuthProfile):
    if profile is None:
        return "You must be logged in with your Hugging Face account.", None, None

    username = profile.username
    user_score = check_user_score(username)

    if not user_score:
        return "You need to complete Unit 4 first.", None, None

    score = user_score["score"]

    if score < THRESHOLD_SCORE:
        return f"Your score is {score}. You need at least {THRESHOLD_SCORE} to pass.", None, None

    certificate_image, certificate_pdf = generate_certificate(name, score)
    add_certificate_entry(username, name, score)
    return "🎉 Congratulations! Here's your certificate:", certificate_image, certificate_pdf

# Gradio UI
with gr.Blocks() as demo:
    gr.Markdown("# 🎓 Agents Course - Get Your Final Certificate")
    gr.Markdown("Welcome! Follow the steps below to receive your official certificate:")
    gr.Markdown("⚠️ **Note**: Due to high demand, you might experience occasional bugs. If something doesn't work, please try again after a moment!")

    with gr.Group():
        gr.Markdown("## ✅ How it works")
        gr.Markdown("""
        1. **Sign in** with your Hugging Face account using the button below.  
        2. **Enter your full name** (this will appear on the certificate).  
        3. Click **'Get My Certificate'** to check your score and download your certificate.
        """)
    gr.Markdown("---")
    gr.Markdown("📝 **Note**: You must have completed [Unit 4](https://huggingface.co/learn/agents-course/unit4/introduction) and your Agent must have scored **above 30** to get your certificate.")

    gr.LoginButton()
    with gr.Row():
        name_input = gr.Text(label="Enter your name (this will appear on the certificate)")
    generate_btn = gr.Button("Get my certificate")
    output_text = gr.Textbox(label="Result")
    cert_image = gr.Image(label="Your Certificate")
    cert_file = gr.File(label="Download Certificate (PDF)", file_types=[".pdf"])

    generate_btn.click(
        fn=handle_certificate,
        inputs=[name_input],
        outputs=[output_text, cert_image, cert_file]
    )

demo.launch()