Update app.py

app.py

@@ -1,30 +1,26 @@
 import gradio as gr
 from huggingface_hub import HfApi, hf_hub_download
 from huggingface_hub.repocard import metadata_load
+from huggingface_hub import HfApi, Repository
 
-import pandas as pd
+import time  
 
 import os
+import pandas as pd
 
 from utils import *
 
 api = HfApi()
 
+DATASET_REPO_URL = "https://huggingface.co/datasets/huggingface-projects/Deep-RL-Course-Certification"
+CERTIFIED_USERS_FILENAME = "certified_users.csv"
+CERTIFIED_USERS_DIR = "certified_users"
 
-import mailchimp_transactional as MailchimpTransactional
-from mailchimp_transactional.api_client import ApiClientError
-
-print(os.environ.get('MAILCHIMP_API_KEY'))
-
-def run():
-  try:
-    mailchimp = MailchimpTransactional.Client(os.environ.get('MAILCHIMP_API_KEY'))
-    response = mailchimp.users.ping()
-    print('API called successfully: {}'.format(response))
-  except ApiClientError as error:
-    print('An exception occurred: {}'.format(error.text))
+HF_TOKEN = os.environ.get("HF_TOKEN")
 
-run()
+repo = Repository(
+    local_dir=CERTIFIED_USERS_DIR, clone_from=DATASET_REPO_URL, use_auth_token=HF_TOKEN
+)
 
 def get_user_models(hf_username, env_tag, lib_tag):
     """
@@ -251,10 +247,95 @@ def certification(hf_username):
     
   print(results_certification)
  
-  df = pd.DataFrame(results_certification)
-  df = df[['passed', 'unit', 'env', 'min_result', 'best_result', 'best_model_id']]
+  df1 = pd.DataFrame(results_certification)
+
+  df = df1[['passed', 'unit', 'env', 'min_result', 'best_result', 'best_model_id']]
+
+  verify_certification(results_certification, hf_username, first_name, last_name)
+
   return df
 
+"""
+Verify that the user pass.
+If yes:
+- Generate the certification
+- Send an email
+- Print the certification
+
+If no:
+- Explain why the user didn't pass yet
+"""
+def verify_certification(df, hf_username, first_name, last_name):
+  # Check that we pass
+  model_pass_nb = 0
+  pass_percentage = 0
+  for unit in df:
+    if unit["passed_"] is True:
+      model_pass_nb += 1
+  
+  pass_percentage = (model_pass_nb/12) * 100 
+  print("pass_percentage", pass_percentage)
+  
+  if pass_percentage == 100:
+    # Generate a certificate of excellence
+    generate_certificate("./certificate_models/certificate-excellence.png", first_name, last_name)
+
+    # Add this user to our database
+    add_certified_user(hf_username, first_name, last_name, pass_percentage)
+    
+    # Output everything in gradio
+
+
+  elif pass_percentage < 100 and pass_percentage >= 80:
+    # Certificate of completion
+    generate_certificate("./certificate_models/certificate-completion.png", first_name, last_name)
+
+    # Add this user to our database
+    add_certified_user(hf_username, first_name, last_name, pass_percentage)
+
+    # Output everything in gradio
+
+  
+  else:
+    # Not pass yet
+    print ("not pass yet")
+
+def generate_certificate(certificate_model, first_name, last_name):
+    im = Image.open(certificate_model)
+    d = ImageDraw.Draw(im)
+
+    name_font = ImageFont.truetype("Quattrocento-Regular.ttf", 100)
+    date_font = ImageFont.truetype("Quattrocento-Regular.ttf", 48)
+    
+    name = first_name + " " + last_name
+    
+    # Debug line name
+    #d.line(((200, 740), (1800, 740)), "gray")
+    #d.line(((1000, 0), (1000, 1400)), "gray")
+    
+    # Name
+    d.text((1000, 740), name, fill="black", anchor="mm", font=name_font)
+
+    # Debug line date
+    #d.line(((1500, 0), (1500, 1400)), "gray")
+
+    # Date of certification
+    d.text((1480, 1170), str(date.today()), fill="black", anchor="mm", font=date_font)
+  
+    im.save("certificate_"+".png")
+
+
+def add_certified_user(hf_username, first_name, last_name, pass_percentage):
+  repo.git_pull()
+  history = pd.read_csv(os.path.join(CERTIFIED_USERS_DIR, CERTIFIED_USERS_FILENAME))
+  new_row = {'hf_username': hf_username, 'first_name': first_name, 'last_name': last_name, 'pass_percentage': pass_percentage, 'datetime': time.time()}
+  new_history = pd.DataFrame(new_row)
+  history = pd.concat([history, new_history])
+  print("HISTORY", history)
+  history.to_csv(os.path.join(CERTIFIED_USERS_DIR, CERTIFIED_USERS_FILENAME), index=False)
+  df.to_csv(os.path.join(CERTIFIED_USERS_DIR, CERTIFIED_USERS_FILENAME), index=False)
+  repo.push_to_hub(commit_message="Update certified users list")
+
 
 with gr.Blocks() as demo:
     gr.Markdown(f"""
@@ -271,10 +352,12 @@ with gr.Blocks() as demo:
     Just type your Hugging Face Username 🤗 (in my case ThomasSimonini)
     """)
     
-    hf_username = gr.Textbox(placeholder="ThomasSimonini", label="Your Hugging Face Username")
-    #email = gr.Textbox(placeholder="[email protected]", label="Your Email (to receive your certificate)")
+    hf_username = gr.Textbox(placeholder="ThomasSimonini", label="Your Hugging Face Username (case sensitive)")
+    first_name = gr.Textbox(placeholder="Jane", label="Your First Name")
+    last_name = gr.Textbox(placeholder="Doe", label="Your Last Name")
+    #email = gr.Textbox(placeholder="[email protected]", label="Your Email (to receive your certificate)")
     check_progress_button = gr.Button(value="Check my progress")
     output = gr.components.Dataframe(value= certification(hf_username), headers=["Pass?", "Unit", "Environment", "Baseline", "Your best result", "Your best model id"], datatype=["markdown", "markdown", "markdown", "number", "number", "markdown", "bool"])
     check_progress_button.click(fn=certification, inputs=hf_username, outputs=output)
 
-demo.launch()
+demo.launch(debug=True)