refactor(agent): remove unused websearch_agent and update supervisor instructions

Remove the unused `websearch_agent` import and tool from supervisor agent configuration, keeping only `web_search_agents`. Update system prompt to instruct the agent to respond immediately once answer is found and avoid unnecessary searching to prevent exceeding action step limits. Also apply code formatting improvements to app.py.

agent/agent.py

@@ -6,7 +6,8 @@ from langchain_core.messages import HumanMessage
 from agent.tools.math_solver import math_solver
 
 from agent.agents.websearchagents import web_search_agents
-from agent.agents.websearchagent import websearch_agent
+
+# from agent.agents.websearchagent import websearch_agent
 from agent.agents.answer_extractor import extract_answer
 
 load_dotenv()
@@ -16,15 +17,19 @@ def supervisor_agent():
     """Return a supervisor agent instance with math_solver and websearch_agent."""
     return create_agent(
         model="google_genai:gemini-3-flash-preview",
-        tools=[math_solver, websearch_agent, web_search_agents],
+        # tools=[math_solver, websearch_agent, web_search_agents],
+        tools=[math_solver, web_search_agents],
         system_prompt=(
             f"You are a supervisor agent. "
             f"Current time is: {datetime.now(timezone.utc).isoformat()}. "
             f"Your memory are out of date. "
             f"For any math or calculation questions, use the math_solver tool for check, "
             f"the accurate is the most important."
-            f"All questions that need real-time, must use the websearch_agent tool "
-            f"to get a concise and accurate final answer."
+            f"All questions that need real-time, must use the web_search_agents tool "
+            f"to get a concise and accurate final answer. "
+            f"Once you have found the answer, respond immediately. "
+            f"Do NOT continue searching or verifying unnecessarily — "
+            f"you have a limited number of action steps and must avoid exceeding them."
         ),
     )
 
@@ -35,7 +40,8 @@ def run(query: str, max_retries: int = 3) -> str:
 
     for attempt in range(1, max_retries + 1):
         print(
-            f"{Fore.CYAN}[Supervisor] Processing query (attempt {attempt}/{max_retries})...{Style.RESET_ALL}"
+            f"{Fore.CYAN}[Supervisor] Processing query (attempt {attempt}/{max_retries})...\n"
+            f"[Supervisor] Query: {query}{Style.RESET_ALL}"
         )
         agent = supervisor_agent()
 

app.py

@@ -1,8 +1,8 @@
 import os
 import gradio as gr
-import requests
+import requests  # type: ignore[import]
 import inspect
-import pandas as pd
+import pandas as pd  # type: ignore[import]
 
 # (Keep Constants as is)
 # --- Constants ---
@@ -11,25 +11,28 @@ DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 # --- Agent Definition ---
 from agent.agent import run as agent_run
 
+
 class BasicAgent:
     def __init__(self):
         print("BasicAgent initialized.")
+
     def __call__(self, question: str) -> str:
         print(f"Agent received question (first 50 chars): {question[:50]}...")
         answer = agent_run(question)
         print(f"Agent returning answer (first 50 chars): {answer[:50]}...")
         return 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
+    space_id = os.getenv("SPACE_ID")  # Get the SPACE_ID for sending link to the code
 
     if profile:
-        username= f"{profile.username}"
+        username = f"{profile.username}"
         print(f"User logged in: {username}")
     else:
         print("User not logged in.")
@@ -56,16 +59,16 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
         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("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"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
@@ -82,18 +85,36 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
             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})
+            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}"})
+            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}
+    # 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)
 
@@ -163,20 +184,19 @@ 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)
+    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)
+    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
+    space_id_startup = os.getenv("SPACE_ID")  # Get SPACE_ID at startup
 
     if space_host_startup:
         print(f"✅ SPACE_HOST found: {space_host_startup}")
@@ -184,14 +204,18 @@ if __name__ == "__main__":
     else:
         print("ℹ️  SPACE_HOST environment variable not found (running locally?).")
 
-    if space_id_startup: # Print repo URLs if SPACE_ID is found
+    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")
+        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(
+            "ℹ️  SPACE_ID environment variable not found (running locally?). Repo URL cannot be determined."
+        )
 
-    print("-"*(60 + len(" App Starting ")) + "\n")
+    print("-" * (60 + len(" App Starting ")) + "\n")
 
     print("Launching Gradio Interface for Basic Agent Evaluation...")
-    demo.launch(debug=True, share=False)
+    demo.launch(debug=True, share=False)