Ensure users are connected to use capabilities

src/eval/submission.py

@@ -13,9 +13,6 @@ def run_and_submit_all(agent, 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}"
         print(f"User logged in: {username}")
@@ -26,18 +23,8 @@ def run_and_submit_all(agent, profile: gr.OAuthProfile | None):
     api_url = DEFAULT_API_URL
     questions_url = f"{api_url}/questions"
     submit_url = f"{api_url}/submit"
-
-    # 1. Instantiate Agent ( modify this part to create your agent)
-    try:
-        agent = agent
-    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"
-    print(agent_code)
-
-    # 2. Fetch Questions
+    
+    # 1. Fetch Questions
     print(f"Fetching questions from: {questions_url}")
     try:
         response = requests.get(questions_url, timeout=15)
@@ -58,7 +45,7 @@ def run_and_submit_all(agent, profile: gr.OAuthProfile | None):
         print(f"An unexpected error occurred fetching questions: {e}")
         return f"An unexpected error occurred fetching questions: {e}", None
 
-    # 3. Run your Agent
+    # 2. Run your Agent
     results_log = []
     answers_payload = []
     is_correct_answers = []
@@ -91,12 +78,12 @@ def run_and_submit_all(agent, profile: gr.OAuthProfile | None):
         print("Agent did not produce any answers to submit.")
         return "Agent did not produce any answers to submit.", pd.DataFrame(results_log)
 
-    # 4. Prepare Submission 
+    # 3. Prepare Submission 
     submission_data = {"username": username.strip(), "agent_code": agent_code, "answers": answers_payload}
     status_update = f"Agent finished. Submitting {len(answers_payload)} answers for user '{username}'..."
     print(status_update)
 
-    # 5. Submit
+    # 4. Submit
     print(f"Submitting {len(answers_payload)} answers to: {submit_url}")
     try:
         response = requests.post(submit_url, json=submission_data, timeout=60)
@@ -140,60 +127,3 @@ def run_and_submit_all(agent, profile: gr.OAuthProfile | None):
         print(status_message)
         results_df = pd.DataFrame(results_log)
         return status_message, results_df
-
-
-
-    # --- Build Gradio Interface using Blocks ---
-    with gr.Blocks() as demo:
-        gr.Markdown("# Basic Agent 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.
-            """
-        )
-
-        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)
-
-        def run_with_login_state(profile: gr.OAuthProfile):
-            return run_and_submit_all(agent, profile)
-
-        run_button.click(
-            fn=run_with_login_state,
-            outputs=[status_output, results_table]
-        )
-
-    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)

src/ui/builder.py

@@ -4,6 +4,7 @@ import re
 import shutil
 from typing import Optional
 import gradio as gr
+from functools import partial
 
 from smolagents.agent_types import AgentAudio, AgentImage, AgentText, handle_agent_output_types
 from smolagents.agents import ActionStep, MultiStepAgent
@@ -162,6 +163,7 @@ def stream_to_gradio(
         yield gr.ChatMessage(role="assistant", content=f"**Final answer:** {str(final_answer)}")
 
 
+
 class GradioUI:
     """A one-line interface to launch your agent in Gradio"""
     def __init__(self, agent: MultiStepAgent, file_upload_folder: str | None = None):
@@ -233,7 +235,14 @@ class GradioUI:
 
         return gr.Textbox(f"File uploaded: {file_path}", visible=True), file_uploads_log + [file_path]
 
-    def log_user_message(self, text_input, file_uploads_log):
+    def log_user_message(self, text_input, file_uploads_log, profile: gr.OAuthProfile | None):
+        if profile:
+            username= f"{profile.username}"
+            print(f"User logged in: {username}")
+        else:
+            print("User not logged in.")
+            return "Please Login to Hugging Face with the button.", None
+
         return (
             text_input
             + (
@@ -254,6 +263,7 @@ class GradioUI:
                 """
             )
             gr.LoginButton()
+            
             gr.Markdown(
                 """
                 ---
@@ -280,12 +290,17 @@ class GradioUI:
                     self.upload_file,
                     [upload_file, file_uploads_log],
                     [upload_status, file_uploads_log],
+                
                 )
             text_input = gr.Textbox(lines=1, label="Chat Message")
+            
+            def log_user_message_with_login_state(text_input, file_uploads_log, profile: gr.OAuthProfile):
+                return self.log_user_message(text_input=text_input, file_uploads_log=file_uploads_log, profile=profile)
+
             text_input.submit(
-                self.log_user_message,
-                [text_input, file_uploads_log],
-                [stored_messages, text_input],
+                fn=log_user_message_with_login_state,
+                inputs=[text_input, file_uploads_log],
+                outputs=[stored_messages, text_input],
             ).then(self.interact_with_agent, [stored_messages, chatbot], [chatbot])
             
             gr.Markdown(