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import gradio as gr
from datasets import load_dataset, Dataset
from datetime import datetime
from datetime import date
import io
import os
from PIL import Image, ImageDraw, ImageFont
from huggingface_hub import login
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
# 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
# Function to check if certificate entry exists
def has_certificate_entry(username):
cert_data = load_dataset(CERTIFICATES_DATASET, split="train", download_mode="force_redownload")
print(username)
return any(row["username"] == username for row in cert_data)
# Function to add certificate entry
def add_certificate_entry(username, name, score):
# Load current dataset
ds = load_dataset(CERTIFICATES_DATASET, split="train", download_mode="force_redownload")
# Remove any existing entry with the same username
filtered_rows = [row for row in ds if row["username"] != username]
# Append the updated/new entry
new_entry = {
"username": username,
"score": score,
"timestamp": datetime.now().isoformat()
}
filtered_rows.append(new_entry)
# Rebuild dataset and push
updated_ds = Dataset.from_list(filtered_rows)
updated_ds.push_to_hub(CERTIFICATES_DATASET)
# Function to generate certificate PDF
def generate_certificate(name, score):
"""Generate certificate image and PDF."""
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"
# Main function to handle certificate generation
def handle_certificate(name, profile: gr.OAuthProfile):
if profile is None:
return "You must be logged in with your Hugging Face account.", 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 interface
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()
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