style

.style.yapf

@@ -0,0 +1,4 @@
+[style]
+based_on_style = google
+indent_width = 2
+

app.py

@@ -10,136 +10,152 @@ import basic_agent
 # --- Constants ---
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 
-def run_and_submit_all( profile: gr.OAuthProfile | None):
-    """
+
+def run_and_submit_all(profile: gr.OAuthProfile | None):
+  """
     Fetches all questions, runs the basic_agent.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:
-        print("This is new code creating the new basic_agent")
-        agent = basic_agent.BasicAgent()
-        print("This is new code creating the new basic_agent is now done")
-    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}")
+  # --- 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:
+    print("This is new code creating the new basic_agent")
+    agent = basic_agent.BasicAgent()
+    print("This is new code creating the new basic_agent is now done")
+  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}")
+  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:
-        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
+      print(f"calling agent")
+      submitted_answer = agent(question_text)
+      print(f"called agent: {submitted_answer=}")
+      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"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:
-            print(f"calling agent")
-            submitted_answer = agent(question_text)
-            print(f"called agent: {submitted_answer=}")
-            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}")
+      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}")
+  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:
-        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
-    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
+      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
+  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
 
 
 # --- Build Gradio Interface using Blocks ---
 with gr.Blocks() as demo:
-    gr.Markdown("# Basic Agent Evaluation Runner")
-    gr.Markdown(
-        """
+  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 ...
@@ -150,44 +166,47 @@ with gr.Blocks() as demo:
         **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()
+  gr.LoginButton()
 
-    run_button = gr.Button("Run Evaluation & Submit All Answers")
+  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)
+  # 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]
-    )
+  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("*"*10, "This is new code!", "*"*10)
-
-    print("Launching Gradio Interface for Basic Agent Evaluation...")
-    demo.launch(debug=True, share=False)
+  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("*" * 10, "This is new code!", "*" * 10)
+
+  print("Launching Gradio Interface for Basic Agent Evaluation...")
+  demo.launch(debug=True, share=False)

basic_agent.py

@@ -4,7 +4,6 @@ import sys
 
 import smolagents
 
-
 LOG = logging.getLogger(__name__)
 
 SYSTEM_PROMPT = """
@@ -13,64 +12,69 @@ You are a general AI assistant. I will ask you a question. Report your thoughts,
 Take the time to plan the steps to reach the solution. Show the steps and then execute the steps.
 """
 
+
 # --- Basic Agent Definition ---
 # ----- THIS IS WERE YOU CAN BUILD WHAT YOU WANT ------
 class BasicAgent:
-    def __init__(self, model_id=None):
-        print("BasicAgent initializing.")
-        # Logs appear to be swallowed.
-        LOG.warning("logging BasicAgent initialized.")
 
-        if model_id:
-          self.model_id = model_id
-        else:
-          #self.model_id = "HuggingFaceTB/SmolLM2-1.7B-Instruct"
-          #self.model_id = "Qwen/Qwen3-4B-FP8"
-          self.model_id = "Qwen/Qwen3-32B"
+  def __init__(self, model_id=None):
+    print("BasicAgent initializing.")
+    # Logs appear to be swallowed.
+    LOG.warning("logging BasicAgent initialized.")
+
+    if model_id:
+      self.model_id = model_id
+    else:
+      #self.model_id = "HuggingFaceTB/SmolLM2-1.7B-Instruct"
+      #self.model_id = "Qwen/Qwen3-4B-FP8"
+      self.model_id = "Qwen/Qwen3-32B"
 
-        # Run locally.
-        #self.model = smolagents.TransformersModel(
-        #  model_id=self.model_id,
-        #  max_new_tokens=32000,
-        #  )
+    # Run locally.
+    #self.model = smolagents.TransformersModel(
+    #  model_id=self.model_id,
+    #  max_new_tokens=32000,
+    #  )
 
-        print("BasicAgent making model.")
-        self.model = smolagents.HfApiModel(
-            max_tokens=32000,
-            temperature=0.3,
-            model_id=self.model_id,
-            custom_role_conversions=None,
-            )
-        self.tools = [smolagents.DuckDuckGoSearchTool(), smolagents.VisitWebpageTool(), smolagents.FinalAnswerTool()]
+    print("BasicAgent making model.")
+    self.model = smolagents.HfApiModel(
+        max_tokens=32000,
+        temperature=0.3,
+        model_id=self.model_id,
+        custom_role_conversions=None,
+    )
+    self.tools = [
+        smolagents.DuckDuckGoSearchTool(),
+        smolagents.VisitWebpageTool(),
+        smolagents.FinalAnswerTool()
+    ]
 
-        print("BasicAgent making search tool.")
-        self.search_agent = smolagents.CodeAgent(
-            name="search_agent",
-            description="Search the web",
-            model=self.model,
-            tools=self.tools,
-            max_steps=6,
-            verbosity_level=2,
-            planning_interval=None,
-            additional_authorized_imports=["duckduckgo_search"],
-            )
+    print("BasicAgent making search tool.")
+    self.search_agent = smolagents.CodeAgent(
+        name="search_agent",
+        description="Search the web",
+        model=self.model,
+        tools=self.tools,
+        max_steps=6,
+        verbosity_level=2,
+        planning_interval=None,
+        additional_authorized_imports=["duckduckgo_search"],
+    )
 
-        print("BasicAgent making manager.")
-        self.manager_agent = smolagents.CodeAgent(
-            name="manager_agent",
-            description="Manger of other agents",
-            tools=[smolagents.FinalAnswerTool()],
-            model=self.model,
-            max_steps=6,
-            verbosity_level=2,
-            planning_interval=None,
-            additional_authorized_imports=["duckduckgo_search"],
-            managed_agents=[self.search_agent]
-            )
+    print("BasicAgent making manager.")
+    self.manager_agent = smolagents.CodeAgent(
+        name="manager_agent",
+        description="Manger of other agents",
+        tools=[smolagents.FinalAnswerTool()],
+        model=self.model,
+        max_steps=6,
+        verbosity_level=2,
+        planning_interval=None,
+        additional_authorized_imports=["duckduckgo_search"],
+        managed_agents=[self.search_agent])
 
-    def __call__(self, question: str) -> str:
-        print(f"NEW Agent received question (first 50 chars): {question[:50]}...")
-        prompt = f"{SYSTEM_PROMPT}\n\n{question}"
-        answer = self.manager_agent.run(prompt)
-        print(f"NEW {answer=}")
-        return answer
+  def __call__(self, question: str) -> str:
+    print(f"NEW Agent received question (first 50 chars): {question[:50]}...")
+    prompt = f"{SYSTEM_PROMPT}\n\n{question}"
+    answer = self.manager_agent.run(prompt)
+    print(f"NEW {answer=}")
+    return answer

basic_agent_test.py

@@ -8,6 +8,8 @@ LOG = logging.getLogger(__name__)
 
 ba = basic_agent.BasicAgent()
 
-answer = ba("Who is the 47th president of the united states? If necessary, use a web search to get the most up to date information.")
+answer = ba(
+    "Who is the 47th president of the united states? If necessary, use a web search to get the most up to date information."
+)
 
 LOG.warning(f"{answer=}")