updated app.py

app.py

@@ -3,51 +3,57 @@ import gradio as gr
 import requests
 import inspect
 import pandas as pd
-
+from smolagents import CodeAgent, DuckDuckGoSearchTool, OpenAIServerModel, PythonInterpreterTool, WikipediaSearchTool, FinalAnswerTool
+ 
 # (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):
+    def __init__(self, api_key: str = None):
+        if not api_key:
+            print("Did not receive API key.")
+        else:
+            print(f"First 5 characters of the provided API key: {api_key[:5]}")
+            os.environ["OPENAI_API_KEY"] = api_key
         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):
+        agent = CodeAgent(tools=[DuckDuckGoSearchTool(),PythonInterpreterTool(),WikipediaSearchTool(),FinalAnswerTool()],model=OpenAIServerModel(model_id="gpt-4o"))
+        answer=agent.run(question)
+        return answer
+ 
+def run_and_submit_all(api_key: str, profile: gr.OAuthProfile | None = 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()
+        agent = BasicAgent(api_key=api_key)
     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:
@@ -68,7 +74,7 @@ def run_and_submit_all( profile: gr.OAuthProfile | 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 = []
@@ -86,16 +92,16 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
         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}")
     try:
@@ -138,59 +144,66 @@ def run_and_submit_all( 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.
         """
     )
-
+ 
+    # Add API Key input field
+    api_key_input = gr.Textbox(
+        label="API Key",
+        placeholder="Enter your OpenAI API key here (sk-...)",
+        type="password"
+    )
     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,
+        inputs=[api_key_input],
         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("Launching Gradio Interface for Basic Agent Evaluation...")
     demo.launch(debug=True, share=False)