Clean up

app.py

@@ -1,15 +1,13 @@
 import os
+
 import gradio as gr
 import requests
-import inspect
 import pandas as pd
 
-# (Keep Constants as is)
-# --- Constants ---
+
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 
-# --- Basic Agent Definition ---
-# ----- THIS IS WERE YOU CAN BUILD WHAT YOU WANT ------
+
 class BasicAgent:
     def __init__(self):
         print("BasicAgent initialized.")
@@ -19,16 +17,14 @@ class BasicAgent:
         print(f"Agent returning fixed answer: {fixed_answer}")
         return fixed_answer
 
-def run_and_submit_all( profile: gr.OAuthProfile | None):
+
+def run_and_submit_all(profile: gr.OAuthProfile | None):
     """
     Fetches all questions, runs the BasicAgent on them, submits all answers,
     and displays the results.
     """
-    # --- Determine HF Space Runtime URL and Repo URL ---
-    space_id = os.getenv("SPACE_ID") # Get the SPACE_ID for sending link to the code
-
     if profile:
-        username= f"{profile.username}"
+        username:str = profile.username
         print(f"User logged in: {username}")
     else:
         print("User not logged in.")
@@ -44,8 +40,8 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
     except Exception as e:
         print(f"Error instantiating agent: {e}")
         return f"Error initializing agent: {e}", None
-    # In the case of an app running as a hugging Face space, this link points toward your codebase ( usefull for others so please keep it public)
-    agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"
+    # In the case of an app running as a HF Space, this link points toward your codebase
+    agent_code = f"https://huggingface.co/spaces/{os.getenv("SPACE_ID")}/tree/main"
     print(agent_code)
 
     # 2. Fetch Questions
@@ -53,7 +49,7 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
     try:
         response = requests.get(questions_url, timeout=15)
         response.raise_for_status()
-        questions_data = response.json()
+        questions_data: list[dict] = response.json()
         if not questions_data:
              print("Fetched questions list is empty.")
              return "Fetched questions list is empty or invalid format.", None
@@ -140,57 +136,38 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
         return status_message, results_df
 
 
-# --- Build Gradio Interface using Blocks ---
+# Demo app
 with gr.Blocks() as demo:
-    gr.Markdown("# Basic Agent Evaluation Runner")
+    gr.Markdown("# Agents Course Final Assignment Evaluation Runner")
     gr.Markdown(
-        """
-        **Instructions:**
-
-        1.  Please clone this space, then modify the code to define your agent's logic, the tools, the necessary packages, etc ...
-        2.  Log in to your Hugging Face account using the button below. This uses your HF username for submission.
-        3.  Click 'Run Evaluation & Submit All Answers' to fetch questions, run your agent, submit answers, and see the score.
-
-        ---
-        **Disclaimers:**
-        Once clicking on the "submit button, it can take quite some time ( this is the time for the agent to go through all the questions).
-        This space provides a basic setup and is intentionally sub-optimal to encourage you to develop your own, more robust solution. For instance for the delay process of the submit button, a solution could be to cache the answers and submit in a seperate action or even to answer the questions in async.
-        """
-    )
+"""\
+**Instructions:**
+1.  Please clone this space, then modify the code to define your agent's logic, the tools, the necessary packages, etc ...
+2.  Log in to your Hugging Face account using the button below. This uses your HF username for submission.
+3.  Click 'Run Evaluation & Submit All Answers' to fetch questions, run your agent, submit answers, and see the score.
+Note: Once clicking on the "submit button, it can take quite some time (this is the time for the agent to go through all the questions).
 
-    gr.LoginButton()
+**Implementation:**
 
+"""
+    )
+    gr.LoginButton()
     run_button = gr.Button("Run Evaluation & Submit All Answers")
-
-    status_output = gr.Textbox(label="Run Status / Submission Result", lines=5, interactive=False)
-    # Removed max_rows=10 from DataFrame constructor
-    results_table = gr.DataFrame(label="Questions and Agent Answers", wrap=True)
-
+    status_output = gr.Textbox(
+        label="Run Status / Submission Result",
+        lines=5,
+        interactive=False
+    )
+    results_table = gr.DataFrame(
+        label="Questions and Agent Answers",
+        wrap=True
+    )
     run_button.click(
         fn=run_and_submit_all,
         outputs=[status_output, results_table]
     )
 
-if __name__ == "__main__":
-    print("\n" + "-"*30 + " App Starting " + "-"*30)
-    # Check for SPACE_HOST and SPACE_ID at startup for information
-    space_host_startup = os.getenv("SPACE_HOST")
-    space_id_startup = os.getenv("SPACE_ID") # Get SPACE_ID at startup
-
-    if space_host_startup:
-        print(f"✅ SPACE_HOST found: {space_host_startup}")
-        print(f"   Runtime URL should be: https://{space_host_startup}.hf.space")
-    else:
-        print("ℹ️  SPACE_HOST environment variable not found (running locally?).")
 
-    if space_id_startup: # Print repo URLs if SPACE_ID is found
-        print(f"✅ SPACE_ID found: {space_id_startup}")
-        print(f"   Repo URL: https://huggingface.co/spaces/{space_id_startup}")
-        print(f"   Repo Tree URL: https://huggingface.co/spaces/{space_id_startup}/tree/main")
-    else:
-        print("ℹ️  SPACE_ID environment variable not found (running locally?). Repo URL cannot be determined.")
-
-    print("-"*(60 + len(" App Starting ")) + "\n")
-
-    print("Launching Gradio Interface for Basic Agent Evaluation...")
-    demo.launch(debug=True, share=False)
+# Run app
+if __name__ == "__main__":
+    demo.launch(debug=True, share=False)