40% scoring overall : need to improve the usage of attached file in questions

app.py

@@ -3,6 +3,7 @@ import gradio as gr
 import requests
 import inspect
 import pandas as pd
+from smolagents import CodeAgent, HfApiModel, DuckDuckGoSearchTool, VisitWebpageTool, OpenAIServerModel
 
 # (Keep Constants as is)
 # --- Constants ---
@@ -12,10 +13,27 @@ DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 # ----- THIS IS WERE YOU CAN BUILD WHAT YOU WANT ------
 class BasicAgent:
     def __init__(self):
+        print("Start BasicAgent initialization.")
+
+        #TODO : define your OpenAI API key
+        self.openai_key = os.getenv("OPENAI_API_KEY")
+
+        self.model = OpenAIServerModel(model_id="o4-mini", api_key=self.openai_key)
+
+        #TODO : change verbosity_level for debug
+        self.agent = CodeAgent(
+            tools=[DuckDuckGoSearchTool(), VisitWebpageTool()],
+            model=self.model,
+            additional_authorized_imports=["helium"],
+            max_steps=10,
+            verbosity_level=1,
+        )
+
         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."
+        fixed_answer = self.agent.run(question)
         print(f"Agent returning fixed answer: {fixed_answer}")
         return fixed_answer
 
@@ -36,6 +54,9 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
 
     api_url = DEFAULT_API_URL
     questions_url = f"{api_url}/questions"
+    #TODO : use only one question for debug
+    #questions_url = f"{api_url}/random-question"
+    
     submit_url = f"{api_url}/submit"
 
     # 1. Instantiate Agent ( modify this part to create your agent)
@@ -52,8 +73,12 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
     print(f"Fetching questions from: {questions_url}")
     try:
         response = requests.get(questions_url, timeout=15)
+        print(f"response.json() = {response.json()}")
         response.raise_for_status()
         questions_data = response.json()
+        # Ensure questions_data is a list. If it's a single question (dict), wrap it in a list
+        if isinstance(questions_data, dict):
+            questions_data = [questions_data]
         if not questions_data:
              print("Fetched questions list is empty.")
              return "Fetched questions list is empty or invalid format.", None
@@ -72,14 +97,46 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
     # 3. Run your Agent
     results_log = []
     answers_payload = []
+    print(f"questions_data = {questions_data}")
     print(f"Running agent on {len(questions_data)} questions...")
     for item in questions_data:
+        print(f"==================================================================")
+        print(f"================ Question {item.get('task_id')} ==================")
+        print(f"==================================================================")
         task_id = item.get("task_id")
         question_text = item.get("question")
+        file_name = item.get("file_name")
+        
         if not task_id or question_text is None:
             print(f"Skipping item with missing task_id or question: {item}")
             continue
+            
         try:
+            # Check if there's a file to download
+            if file_name:
+                print(f"Question has an attached file: {file_name}")
+                # Construct the file download URL
+                file_url = f"{api_url}/file/{task_id}"
+                try:
+                    # Download the file
+                    file_response = requests.get(file_url, timeout=30)
+                    file_response.raise_for_status()
+                    
+                    # Create temporary directory if it doesn't exist
+                    os.makedirs("temp_files", exist_ok=True)
+                    
+                    # Save the file locally
+                    file_path = os.path.join("temp_files", file_name)
+                    with open(file_path, "wb") as f:
+                        f.write(file_response.content)
+                    
+                    # Modify the question to include information about the attached file
+                    question_text = f"{question_text}\n\nI've attached a file named '{file_name}' that you can find at the path: {file_path}"
+                    print(f"Downloaded file to {file_path}")
+                except Exception as e:
+                    print(f"Error downloading file for task {task_id}: {e}")
+                    question_text = f"{question_text}\n\nNote: There was supposed to be an attached file named '{file_name}', but it couldn't be downloaded: {e}"
+            
             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})

requirements.txt

@@ -1,2 +1,6 @@
 gradio
-requests
+requests
+gradio[oauth]
+smolagents
+duckduckgo_search
+smolagents[openai]