Update app.py

app.py

@@ -1,46 +1,25 @@
 import os
 import gradio as gr
 import requests
-import inspect # To get source code for __repr__
+import inspect
 import pandas as pd
 
+# (Keep Constants and BasicAgent class as is)
 # --- Constants ---
-DEFAULT_API_URL = "https://jofthomas-unit4-scoring.hf.space/" # Default URL for your FastAPI app
+DEFAULT_API_URL = "https://jofthomas-unit4-scoring.hf.space/"
 
 # --- Basic Agent Definition ---
-## This is where you should implement your own agent and tools
-
 class BasicAgent:
-    """
-    A very simple agent placeholder.
-    It just returns a fixed string for any question.
-    """
+    # ... (keep agent code as is) ...
     def __init__(self):
         print("BasicAgent initialized.")
-        # Add any setup if needed
-
     def __call__(self, question: str) -> str:
-        """
-        The agent's logic to answer a question.
-        This basic version ignores the question content.
-        """
         print(f"Agent received question (first 50 chars): {question[:50]}...")
-        # Replace this with actual logic if you were building a real agent
         fixed_answer = "This is a default answer."
         print(f"Agent returning fixed answer: {fixed_answer}")
         return fixed_answer
-
-    # __repr__ seems intended to get the *source* code, not just representation
-    # Let's keep it but note that get_current_script_content might be more robust
-    # if the class definition changes significantly or relies on external state.
     def __repr__(self) -> str:
-        """
-        Return the source code required to reconstruct this agent.
-        NOTE: This might be brittle. Using get_current_script_content is likely safer.
-        """
-        imports = [
-            "import inspect\n"
-        ]
+        imports = ["import inspect\n"]
         try:
             class_source = inspect.getsource(BasicAgent)
             full_source = "\n".join(imports) + "\n" + class_source
@@ -51,17 +30,14 @@ class BasicAgent:
 
 # --- Gradio UI and Logic ---
 def get_current_script_content() -> str:
-    """Attempts to read and return the content of the currently running script."""
+    # ... (keep function as is) ...
     try:
-        # __file__ holds the path to the current script
         script_path = os.path.abspath(__file__)
         print(f"Reading script content from: {script_path}")
         with open(script_path, 'r', encoding='utf-8') as f:
             return f.read()
     except NameError:
-        # __file__ is not defined (e.g., running in an interactive interpreter or frozen app)
         print("Warning: __file__ is not defined. Cannot read script content this way.")
-        # Fallback or alternative method could be added here if needed
         return "# Agent code unavailable: __file__ not defined"
     except FileNotFoundError:
         print(f"Warning: Script file '{script_path}' not found.")
@@ -76,17 +52,27 @@ 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 URL and Print Environment Info ---
+    # --- Determine HF Space Runtime URL and Repo URL ---
     space_host = os.getenv("SPACE_HOST")
-    hf_space_url = "Runtime: Locally or unknown environment (SPACE_HOST env var not found)"
+    space_id = os.getenv("SPACE_ID") # Get the SPACE_ID
+
+    hf_runtime_url = "Runtime: Locally or unknown environment (SPACE_HOST not found)"
+    hf_repo_url = "HF Repo URL: Unknown (SPACE_ID not found)"
+    hf_repo_tree_url = "HF Repo Tree URL: Unknown (SPACE_ID not found)"
+
     if space_host:
-         # Construct the standard URL format for HF Spaces
-         hf_space_url = f"Runtime: Hugging Face Space (https://{space_host}.hf.space)"
+         hf_runtime_url = f"Runtime URL: https://{space_host}.hf.space"
+
+    if space_id: # Construct URLs using SPACE_ID
+        hf_repo_url = f"HF Repo URL: https://huggingface.co/spaces/{space_id}"
+        hf_repo_tree_url = f"HF Repo Tree URL: https://huggingface.co/spaces/{space_id}/tree/main"
 
-    # Print runtime info at the start of the function execution
+    # Print runtime and repo info at the start
     print("\n" + "="*60)
     print("Executing run_and_submit_all function...")
-    print(hf_space_url) # Print the determined runtime URL
+    print(hf_runtime_url) # Print the runtime URL (from SPACE_HOST)
+    print(hf_repo_url)    # Print the base repo URL (from SPACE_ID)
+    print(hf_repo_tree_url) # Print the repo tree URL (from SPACE_ID)
     # --- End Environment Info ---
 
     if profile:
@@ -94,110 +80,80 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
         print(f"User logged in: {username}")
     else:
         print("User not logged in.")
-        print("="*60 + "\n") # Close the separator block
-        return "Please Login to Hugging Face with the button.", None # Return early
+        print("="*60 + "\n")
+        return "Please Login to Hugging Face with the button.", None
 
-    print("="*60 + "\n") # Separator after initial checks if logged in
+    print("="*60 + "\n")
 
+    # ... (rest of the function remains the same) ...
     api_url = DEFAULT_API_URL
     questions_url = f"{api_url}/questions"
     submit_url = f"{api_url}/submit"
 
-    # 1. Instantiate the Agent
+    # 1. Instantiate Agent
     try:
         agent = BasicAgent()
-        # Using get_current_script_content() is likely more reliable for submission
-        # agent_code = agent.__repr__() # Keep if needed, but prefer file content
-        # print(f"Agent Code via __repr__ (first 200): {agent_code[:200]}...") # Debug
     except Exception as e:
         print(f"Error instantiating agent: {e}")
         return f"Error initializing agent: {e}", None
-
-    # Get agent code by reading the current script file - generally more robust
     agent_code = get_current_script_content()
     if agent_code.startswith("# Agent code unavailable"):
         print("Warning: Using potentially incomplete agent code due to reading error.")
-        # Optional: Fall back to agent.__repr__() if needed
-        # agent_code = agent.__repr__()
 
-    # 2. Fetch All Questions
+    # 2. Fetch Questions
     print(f"Fetching questions from: {questions_url}")
     try:
         response = requests.get(questions_url, timeout=15)
-        response.raise_for_status() # Raise HTTPError for bad responses (4xx or 5xx)
+        response.raise_for_status()
         questions_data = response.json()
         if not questions_data:
              print("Fetched questions list is empty.")
              return "Fetched questions list is empty or invalid format.", None
         print(f"Fetched {len(questions_data)} questions.")
-        # status_update = f"Fetched {len(questions_data)} questions. Running agent..." # For yield/streaming
     except requests.exceptions.RequestException as e:
         print(f"Error fetching questions: {e}")
         return f"Error fetching questions: {e}", None
     except requests.exceptions.JSONDecodeError as e:
          print(f"Error decoding JSON response from questions endpoint: {e}")
-         print(f"Response text: {response.text[:500]}") # Log response text for debugging
+         print(f"Response text: {response.text[:500]}")
          return f"Error decoding server response for questions: {e}", None
-    except Exception as e: # Catch other potential errors
+    except Exception as e:
         print(f"An unexpected error occurred fetching questions: {e}")
         return f"An unexpected error occurred fetching questions: {e}", None
 
-    # 3. Run Agent on Each Question
-    results_log = [] # To store data for the results table
-    answers_payload = [] # To store data for the submission API
+    # 3. Run Agent
+    results_log = []
+    answers_payload = []
     print(f"Running agent on {len(questions_data)} questions...")
     for item in questions_data:
         task_id = item.get("task_id")
         question_text = item.get("question")
-
         if not task_id or question_text is None:
             print(f"Skipping item with missing task_id or question: {item}")
             continue
-
         try:
-            submitted_answer = agent(question_text) # Call the agent's logic
-            answers_payload.append({
-                "task_id": task_id,
-                "submitted_answer": submitted_answer
-            })
-            results_log.append({
-                "Task ID": task_id,
-                "Question": question_text,
-                "Submitted Answer": submitted_answer
-            })
+            submitted_answer = agent(question_text)
+            answers_payload.append({"task_id": task_id, "submitted_answer": submitted_answer})
+            results_log.append({"Task ID": task_id, "Question": question_text, "Submitted Answer": submitted_answer})
         except Exception as e:
              print(f"Error running agent on task {task_id}: {e}")
-             results_log.append({
-                "Task ID": task_id,
-                "Question": question_text,
-                "Submitted Answer": f"AGENT ERROR: {e}"
-            })
-             # Decide if you want to submit agent errors or skip:
-             # answers_payload.append({"task_id": task_id, "submitted_answer": f"AGENT ERROR: {e}"})
+             results_log.append({"Task ID": task_id, "Question": question_text, "Submitted Answer": f"AGENT ERROR: {e}"})
 
     if not answers_payload:
         print("Agent did not produce any answers to submit.")
-        # Still show results log even if nothing submitted
         return "Agent did not produce any answers to submit.", pd.DataFrame(results_log)
 
     # 4. Prepare Submission
-    submission_data = {
-        "username": username.strip(),
-        "agent_code": agent_code, # Using the code read from file
-        "answers": answers_payload
-    }
+    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 to Leaderboard
+    # 5. Submit
     print(f"Submitting {len(answers_payload)} answers to: {submit_url}")
     try:
-        # Ensure submission_data is serializable, agent_code should be string
-        response = requests.post(submit_url, json=submission_data, timeout=60) # Increased timeout further
+        response = requests.post(submit_url, json=submission_data, timeout=60)
         response.raise_for_status()
         result_data = response.json()
-
-        # Prepare final status message and results table
         final_status = (
             f"Submission Successful!\n"
             f"User: {result_data.get('username')}\n"
@@ -208,19 +164,16 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
         print("Submission successful.")
         results_df = pd.DataFrame(results_log)
         return final_status, results_df
-
     except requests.exceptions.HTTPError as e:
         error_detail = f"Server responded with status {e.response.status_code}."
         try:
-            # Try to get more specific error detail from JSON response body
             error_json = e.response.json()
             error_detail += f" Detail: {error_json.get('detail', e.response.text)}"
         except requests.exceptions.JSONDecodeError:
-            # If response is not JSON, use the raw text
-            error_detail += f" Response: {e.response.text[:500]}" # Limit length
+            error_detail += f" Response: {e.response.text[:500]}"
         status_message = f"Submission Failed: {error_detail}"
         print(status_message)
-        results_df = pd.DataFrame(results_log) # Show attempts even if submission failed
+        results_df = pd.DataFrame(results_log)
         return status_message, results_df
     except requests.exceptions.Timeout:
         status_message = "Submission Failed: The request timed out."
@@ -232,7 +185,7 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
         print(status_message)
         results_df = pd.DataFrame(results_log)
         return status_message, results_df
-    except Exception as e: # Catch unexpected errors during submission phase
+    except Exception as e:
         status_message = f"An unexpected error occurred during submission: {e}"
         print(status_message)
         results_df = pd.DataFrame(results_log)
@@ -243,7 +196,7 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
 with gr.Blocks() as demo:
     gr.Markdown("# Basic Agent Evaluation Runner")
     gr.Markdown(
-        "Please clone this space, then modify the code to define your agent's logic within the `BasicAgent` class. " # Clarified instructions
+        "Please clone this space, then modify the code to define your agent's logic within the `BasicAgent` class. "
         "Log in to your Hugging Face account using the button below. This uses your HF username for submission. "
         "Click 'Run Evaluation & Submit All Answers' to fetch questions, run your agent, submit answers, and see the score."
     )
@@ -253,28 +206,34 @@ with gr.Blocks() as demo:
     run_button = gr.Button("Run Evaluation & Submit All Answers")
 
     status_output = gr.Textbox(label="Run Status / Submission Result", lines=5, interactive=False)
-    results_table = gr.DataFrame(label="Questions and Agent Answers", wrap=True) 
+    # Removed max_rows=10 from DataFrame constructor
+    results_table = gr.DataFrame(label="Questions and Agent Answers", wrap=True)
 
-    # --- Component Interaction ---
-    # Use the profile information directly from the LoginButton state (implicitly passed)
     run_button.click(
         fn=run_and_submit_all,
-        # Input is implicitly the profile data from LoginButton state
         outputs=[status_output, results_table]
     )
 
 if __name__ == "__main__":
     print("\n" + "-"*30 + " App Starting " + "-"*30)
-    # Check for SPACE_HOST at startup for information
+    # 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"   App should be available at: https://{space_host_startup}.hf.space")
+        print(f"   Runtime URL should be: https://{space_host_startup}.hf.space")
     else:
-        print("ℹ️  SPACE_HOST environment variable not found (running locally or not on standard HF Space runtime).")
-        print("   App will likely be available at local URLs printed by Gradio below.")
+        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...")
-    # Set share=False as the primary access point is the HF Space URL
     demo.launch(debug=True, share=False)