Update app.py

app.py

@@ -1,196 +1,187 @@
-import os
+
+# This code was generated by generate_space_code.py
+# Add this to your Hugging Face Space to use your agent's answers
+
+# Import necessary libraries
 import gradio as gr
+import json
+import os
 import requests
-import inspect
+from huggingface_hub import HfApi
 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.")
-    def __call__(self, question: str) -> str:
-        print(f"Agent received question (first 50 chars): {question[:50]}...")
-        fixed_answer = "This is a default answer."
-        print(f"Agent returning fixed answer: {fixed_answer}")
-        return fixed_answer
-
-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}"
-        print(f"User logged in: {username}")
-    else:
-        print("User not logged in.")
-        return "Please Login to Hugging Face with the button.", 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 = BasicAgent()
-    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
-    print(f"Fetching questions from: {questions_url}")
+# Your agent's answers
+ANSWERS = [
+    {
+        "task_id": "8e867cd7-cff9-4e6c-867a-ff5ddc2550be",
+        "submitted_answer": "According to Mercedes Sosa's discography on her English Wikipedia page, she published three studio albums between 2000 and 2009: \n1. Ac\u00fastico (2002)\n2. Coraz\u00f3n Libre (2005) \n3. Cantora 1 (2009)"
+    },
+    {
+        "task_id": "a1e91b78-d3d8-4675-bb8d-62741b4b68a6",
+        "submitted_answer": "I apologize, but after searching for information, I do not have enough context to determine the highest number of bird species shown simultaneously in the specific YouTube video you linked. The search results did not provide a direct answer or the details needed to infer the answer.\n\nThe most relevant search result was the video title and description itself: \"Emperor Penguin Chicks and Adelie Penguins stand up to Giant Petrel\". This suggests the video shows at least 3 bird species - emperor penguins, adelie penguins, and a giant petrel. However, without watching the full video, I cannot confirm if all 3 species actually appear on camera at the same time, or if there are any additional species shown.\n\nThe other search results discuss bird species counts in general, but do not contain information specific to the video in question. To get a definitive answer, a human would need to watch the entire video, identify all the bird species, and note the maximum number of distinct species visible in a single frame.\n\nAs an AI system without the ability to view and analyze video content directly, I do not have enough information to provide the specific number you're looking for. I apologize I could not be more helpful in answering this question! Let me know if there are other topics I can assist with that do not rely on external video analysis."
+    },
+    {
+        "task_id": "2d83110e-a098-4ebb-9987-066c06fa42d0",
+        "submitted_answer": "right"
+    },
+    {
+        "task_id": "cca530fc-4052-43b2-b130-b30968d8aa44",
+        "submitted_answer": "I apologize, but I am unable to provide the correct next move for black, as no chess position image has been successfully uploaded to our conversation yet. Without being able to see the specific arrangement of pieces on the board, I do not have enough information to analyze the position and determine the move that would guarantee a win for black. Please try uploading the image again. I'd be happy to take a look and provide a detailed answer, including the best move in algebraic notation, once I'm able to examine the position visually. Let me know if you need any assistance with the image upload or if there are any other chess questions I can assist with in the meantime!"
+    },
+    {
+        "task_id": "4fc2f1ae-8625-45b5-ab34-ad4433bc21f8",
+        "submitted_answer": "The Wikipedia user FunkMonk nominated the article \"Anchiornis\", the only Featured Article on English Wikipedia about a dinosaur that was promoted in November 2016. FunkMonk was an active editor of extinct animal articles on Wikipedia at the time and discussed his interest in this topic in a 2016 Wikimedia blog post."
+    },
+    {
+        "task_id": "6f37996b-2ac7-44b0-8e68-6d28256631b4",
+        "submitted_answer": "a, b, c, e"
+    },
+    {
+        "task_id": "9d191bce-651d-4746-be2d-7ef8ecadb9c2",
+        "submitted_answer": "Based on a brief mention in a Reddit post, it seems that when asked \"Isn't that hot?\" in reference to quickly drinking a large amount of coffee, the character Teal'c from Stargate SG-1 replied \"Extremely.\" \n\nHowever, without being able to watch the actual video clip to verify the dialogue and see the full context of the scene, I do not have enough confidence to state this as a definitive answer. The provided search results are quite limited and do not allow me to thoroughly confirm the details of this specific exchange. More context from the episode would be needed to comprehensively answer the question."
+    },
+    {
+        "task_id": "cabe07ed-9eca-40ea-8ead-410ef5e83f91",
+        "submitted_answer": "Based on the information provided in the search results, the surname of the equine veterinarian mentioned in exercise set 1.E of the specified LibreText Introductory Chemistry materials cannot be determined. The search excerpts do not contain the full text of the exercises or any clear references to a veterinarian's name. Without access to the complete original source material, there is insufficient evidence to identify the requested surname. The query cannot be satisfactorily answered given the available information."
+    },
+    {
+        "task_id": "3cef3a44-215e-4aed-8e3b-b1e3f08063b7",
+        "submitted_answer": "Here is the list of vegetables, botanically speaking, from your grocery list in alphabetical order:\n\nacorns, broccoli, celery, lettuce, sweet potatoes"
+    },
+    {
+        "task_id": "99c9cc74-fdc8-46c6-8f8d-3ce2d3bfeea3",
+        "submitted_answer": "I apologize, but I am unable to provide the list of filling ingredients you requested because the \"Strawberry pie.mp3\" audio file containing the recipe was not attached or accessible. Without being able to listen to the recording of your friend Aditi's recipe, I do not have the necessary information to transcribe the instructions and extract the ingredients list. Please try uploading the audio file again. I'll be happy to list out the filling ingredients alphabetically, without measurements, in a comma-separated format once I can successfully access and listen to the recipe. Just let me know when you've attached the file. Thank you for understanding!"
+    },
+    {
+        "task_id": "305ac316-eef6-4446-960a-92d80d542f82",
+        "submitted_answer": "Based on the limited information I was able to find from the provided search results, I do not have enough reliable evidence to determine if Bart\u0142omiej Kasprzykowski, the actor who played Roman in the Polish version of Everybody Loves Raymond, had a role in the series Magda M. I was unable to find any credible sources confirming his involvement in Magda M. or the name of a character he may have played. It's possible he did not appear in Magda M. at all. Without more definitive information, I do not have an answer to the question. I would need to do additional research in Polish-language sources or industry databases to have a chance of finding a reliable answer."
+    },
+    {
+        "task_id": "f918266a-b3e0-4914-865d-4faa564f1aef",
+        "submitted_answer": "I apologize, but I am unable to determine the final numeric output from the Python code because no code file was actually provided with the original question. \n\nTo analyze code and determine its output, I would need to have the actual Python code file shared with me first. It seems in this case that the question referenced an \"attached\" code file, but no file was successfully attached or included.\n\nWithout being able to review the contents of the code, there is no way for me to reason about what the code does or what numeric value it ultimately outputs when run. The code itself is a critical piece of information needed to answer this question.\n\nIn summary, no Python code was provided, so it is not possible to determine the final numeric output. The question cannot be answered without first obtaining the code file that the question refers to. I would recommend asking the question asker to try uploading or sending the actual Python code file again so that it can be properly analyzed to determine the numeric output."
+    },
+    {
+        "task_id": "3f57289b-8c60-48be-bd80-01f8099ca449",
+        "submitted_answer": "In the 1977 regular season, New York Yankees right fielder Reggie Jackson led the team with 78 walks and had 525 at bats, the 4th highest total on the club that year. As an everyday player known for his keen batting eye, Jackson's high number of at bats gave him the plate appearances needed to draw walks at a strong rate and pace the Yankees in that category for the season."
+    },
+    {
+        "task_id": "1f975693-876d-457b-a649-393859e79bf3",
+        "submitted_answer": "I apologize for the inconvenience, but it appears that the \"Homework.mp3\" audio file you referenced was not successfully attached or included with your original request. Without being able to listen to the recording of Professor Willowbrook specifying the pages to review, I unfortunately do not have the information needed to provide the comma-delimited list of page numbers you asked for. \n\nWhen you have a chance, please try uploading the MP3 file again. Once I'm able to access and listen to the audio recording, I'll be happy to let you know the pages your professor recommended studying for the upcoming Calculus mid-term exam, formatted as a list in ascending order as you requested.\n\nPlease let me know if you have any other questions! I'm here to help however I can as you prepare for your test. Wishing you a speedy recovery and all the best with your studies."
+    },
+    {
+        "task_id": "840bfca7-4f7b-481a-8794-c560c340185d",
+        "submitted_answer": "According to the paper \"SOFIA/HAWC+ and Spitzer/IRAC Observations of Galactic Center Filaments\" by T. Pillai et al., which is linked in the Universe Today article \"There Are Hundreds of Mysterious Filaments at the Center of the Milky Way\" by Carolyn Collins Petersen published on June 6, 2023, the work performed by co-author R. G. Arendt was supported by NASA under award number 80GSFC21M0002."
+    },
+    {
+        "task_id": "bda648d7-d618-4883-88f4-3466eabd860e",
+        "submitted_answer": "Saint Petersburg"
+    },
+    {
+        "task_id": "cf106601-ab4f-4af9-b045-5295fe67b37d",
+        "submitted_answer": "I searched for information on athlete participation by country at the 1928 Summer Olympics, but the search results so far do not provide a definitive answer to the question of which country had the fewest athletes. The key information I'm still missing includes:\n\n1. A complete list of how many athletes each country sent to the 1928 Olympics. The search results mention some overall statistics about the Games but do not break it down by country.\n\n2. Confirmation of which countries actually participated in 1928. The results mention the Games were held in Amsterdam but don't specify all the countries that took part.\n\n3. A list of the IOC 3-letter country codes for the countries that participated, which I would need to provide the answer in the requested format and break any ties alphabetically.\n\nTo conclusively answer the question, I would need to find an authoritative source, likely from the IOC or a reputable Olympic history database, that lists the athlete delegation size for each country at the 1928 Games. I would also need the standardized IOC codes for each of those countries.\n\nWithout that key information, I don't feel I have enough evidence yet to provide a definitive answer to the original question. The search results help provide useful context about the 1928 Olympics in general, but more specific data is needed to determine which country had the fewest athletes and give their IOC code as the final answer."
+    },
+    {
+        "task_id": "a0c07678-e491-4bbc-8f0b-07405144218f",
+        "submitted_answer": "Based on the information found in the provided search results, I do not have enough evidence to conclusively determine which specific pitchers have the uniform numbers before and after Taish\u014d Tamai as of July 2023. The search results confirm Tamai currently plays for the Hokkaido Nippon-Ham Fighters but do not specify his uniform number or the surrounding pitchers. Without this key piece of information, I cannot provide the requested before and after pitcher names. I would need to do additional research beyond these search results to find Tamai's 2023 uniform number in order to answer the question."
+    },
+    {
+        "task_id": "7bd855d8-463d-4ed5-93ca-5fe35145f733",
+        "submitted_answer": "I apologize, but based on the search results provided, there is not enough information to answer the original question about calculating the total food sales for a specific fast-food chain from an attached Excel file.\n\nThe search results discuss general fast food industry trends and projections, but do not contain any data from an Excel file with sales figures for a particular fast-food chain's menu items. Without access to that specific Excel file referenced in the original question, it is not possible to calculate the total sales the chain made from food, excluding drinks.\n\nTo comprehensively answer this question, the attached Excel file with the relevant sales data broken out by menu item would need to be provided. Only then could the food sales be totaled up in USD (to two decimal places) while excluding any drink items. But since that necessary data file was not successfully attached or included in the search results, there is insufficient information to answer the original question as stated.\n\nI would recommend requesting that the Excel file be re-sent or re-attached in order to have the data needed to calculate the fast-food chain's total food sales as originally asked. Apologies I could not provide a more complete answer without access to that file. Please let me know if the Excel file with the menu item sales data can be provided."
+    },
+    {
+        "task_id": "5a0c1adf-205e-4841-a666-7c3ef95def9d",
+        "submitted_answer": "Based on the information gathered, I was unable to conclusively determine the first name of a Malko Competition winner from 1977-2000 whose nationality is a defunct country. The winner records from the Malko Competition's official website do not show any recipients in that time period from countries that have since dissolved, such as the USSR, Yugoslavia or Czechoslovakia. It's possible this information exists in other sources not covered in these search results. But without additional evidence pointing to a specific winner and defunct country, I do not have enough facts to provide the requested first name. The question cannot be satisfactorily answered based solely on the data available here."
+    }
+]
+
+def get_username():
+    """Get the username of the logged-in user"""
     try:
-        response = requests.get(questions_url, timeout=15)
-        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.")
-    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]}")
-         return f"Error decoding server response for questions: {e}", None
-    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 your 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)
-            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}"})
-
-    if not answers_payload:
-        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 
-    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
-    print(f"Submitting {len(answers_payload)} answers to: {submit_url}")
+        return os.environ.get("SPACE_AUTHOR")
+    except:
+        return None
+
+def check_login_status():
+    """Check if the user is logged in"""
+    username = get_username()
+    if username:
+        return f"Logged in as {username}"
+    else:
+        return "Not logged in. Please log in to submit."
+
+def run_and_submit_all():
+    """Run the agent on all questions and submit the answers"""
+    username = get_username()
+    if not username:
+        return "Please log in to submit your answers.", None
+    
+    # Get the Space name
+    space_name = os.environ.get("SPACE_ID", "")
+    
+    # Create the code URL
+    code_url = f"https://huggingface.co/spaces/{space_name}/tree/main"
+    
+    # Submit to the API
     try:
-        response = requests.post(submit_url, json=submission_data, timeout=60)
-        response.raise_for_status()
-        result_data = response.json()
-        final_status = (
-            f"Submission Successful!\n"
-            f"User: {result_data.get('username')}\n"
-            f"Overall Score: {result_data.get('score', 'N/A')}% "
-            f"({result_data.get('correct_count', '?')}/{result_data.get('total_attempted', '?')} correct)\n"
-            f"Message: {result_data.get('message', 'No message received.')}"
-        )
-        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:
-            error_json = e.response.json()
-            error_detail += f" Detail: {error_json.get('detail', e.response.text)}"
-        except requests.exceptions.JSONDecodeError:
-            error_detail += f" Response: {e.response.text[:500]}"
-        status_message = f"Submission Failed: {error_detail}"
-        print(status_message)
-        results_df = pd.DataFrame(results_log)
-        return status_message, results_df
-    except requests.exceptions.Timeout:
-        status_message = "Submission Failed: The request timed out."
-        print(status_message)
-        results_df = pd.DataFrame(results_log)
-        return status_message, results_df
-    except requests.exceptions.RequestException as e:
-        status_message = f"Submission Failed: Network error - {e}"
-        print(status_message)
-        results_df = pd.DataFrame(results_log)
-        return status_message, results_df
+        api_url = "https://agents-course-unit4-scoring.hf.space/submit"
+        payload = {
+            "username": username,
+            "agent_code": code_url,
+            "answers": ANSWERS
+        }
+        
+        response = requests.post(api_url, json=payload)
+        
+        if response.status_code == 200:
+            result = response.json()
+            
+            # Create a DataFrame for display
+            data = []
+            for item in result.get("data", []):
+                data.append({
+                    "Task ID": item.get("task_id", ""),
+                    "Question": item.get("question", ""),
+                    "Your Answer": item.get("submitted_answer", ""),
+                    "Correct": item.get("is_correct", False)
+                })
+            
+            df = pd.DataFrame(data)
+            
+            # Calculate score
+            correct_count = sum(1 for item in result.get("data", []) if item.get("is_correct", False))
+            total_count = len(result.get("data", []))
+            score = (correct_count / total_count) * 100 if total_count > 0 else 0
+            
+            submission_result = f"Score: {score:.2f}% ({correct_count}/{total_count} correct)"
+            
+            return submission_result, df
+        else:
+            return f"Error: {response.status_code} - {response.text}", None
     except Exception as e:
-        status_message = f"An unexpected error occurred during submission: {e}"
-        print(status_message)
-        results_df = pd.DataFrame(results_log)
-        return status_message, results_df
+        return f"Error: {str(e)}", None
 
-
-# --- Build Gradio Interface using Blocks ---
+# Create the Gradio interface
 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)
-
-    run_button.click(
-        fn=run_and_submit_all,
-        outputs=[status_output, results_table]
-    )
-
+    gr.Markdown("# GAIA Benchmark Submission")
+    gr.Markdown("This Space submits your agent's answers to the GAIA benchmark leaderboard.")
+    
+    with gr.Row():
+        login_status = gr.Textbox(label="Login Status", value=check_login_status())
+        refresh_btn = gr.Button("Refresh Login Status")
+    
+    with gr.Row():
+        submit_btn = gr.Button("Run and Submit All")
+    
+    with gr.Row():
+        result_text = gr.Textbox(label="Run Status / Submission Result")
+    
+    with gr.Row():
+        result_df = gr.Dataframe(label="Questions and Agent Answers")
+    
+    # Set up event handlers
+    refresh_btn.click(check_login_status, inputs=[], outputs=[login_status])
+    submit_btn.click(run_and_submit_all, inputs=[], outputs=[result_text, result_df])
+
+# Launch the app
 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)
+    demo.launch()