Update app.py

app.py

@@ -3,28 +3,30 @@ import gradio as gr
 import requests
 import pandas as pd
 
-# --- Import your new agent ---
+# Import your upgraded agent
 from agent import GeminiAgent
 
 # --- Constants ---
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
-MY_HF_USERNAME = "benjipeng" # Your Hugging Face username
+# This is the security gate. Only this user can run submissions.
+MY_HF_USERNAME = "benjipeng"
 
 def run_and_submit_all(profile: gr.OAuthProfile | None):
     """
     Fetches all questions, runs the GeminiAgent on them, submits all answers,
-    and displays the results. This function is restricted to a specific user.
+    and displays the results. This function is restricted to a specific user and
+    provides file context to the agent.
     """
     # --- Determine HF Space Runtime URL and Repo URL ---
     space_id = os.getenv("SPACE_ID")
 
+    # --- User Authentication and Authorization ---
     if not profile:
         return "Please Login to Hugging Face with the button to run the evaluation.", None
     
     username = profile.username
     print(f"User logged in: {username}")
 
-    # --- NEW: Restrict submission to a specific user ---
     if username != MY_HF_USERNAME:
         print(f"Access denied for user: {username}. Allowed user is {MY_HF_USERNAME}.")
         return f"Error: This Space is configured for a specific user. Access denied for '{username}'.", None
@@ -33,8 +35,7 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
     questions_url = f"{api_url}/questions"
     submit_url = f"{api_url}/submit"
 
-    # 1. Instantiate your GeminiAgent
-    # The agent will fail to initialize if the GEMINI_API_KEY secret is not set.
+    # 1. Instantiate Agent
     print("Instantiating agent...")
     try:
         agent = GeminiAgent()
@@ -66,18 +67,30 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
          print(f"Response text: {response.text[:500]}")
          return error_msg, None
 
-    # 3. Run your Agent
+    # 3. Run your Agent (with context injection)
     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")
+        
+        # This is the key improvement: check if a file is associated with the question
+        has_file = item.get("file", None) is not None
+        
         if not task_id or question_text is None:
             print(f"Skipping item with missing task_id or question: {item}")
             continue
+
+        # Modify the question to give the agent context about the file's existence
+        if has_file:
+            modified_question = f"{question_text}\n\n[Agent Note: A file is attached to this question. Use the 'read_file_from_api' tool to access it if needed.]"
+        else:
+            modified_question = question_text
+
         try:
-            submitted_answer = agent(question_text)
+            # Pass BOTH the modified question and the task_id to the agent
+            submitted_answer = agent(modified_question, task_id)
             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:
@@ -95,7 +108,7 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
     # 5. Submit
     print(f"Submitting {len(answers_payload)} answers to: {submit_url}")
     try:
-        response = requests.post(submit_url, json=submission_data, timeout=60)
+        response = requests.post(submit_url, json=submission_data, timeout=120) # Increased timeout
         response.raise_for_status()
         result_data = response.json()
         final_status = (
@@ -125,21 +138,19 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
         results_df = pd.DataFrame(results_log)
         return status_message, results_df
 
-
-# --- Build Gradio Interface using Blocks (No changes needed here) ---
+# --- Build Gradio Interface using Blocks ---
 with gr.Blocks() as demo:
-    gr.Markdown("# Gemini Agent Evaluation Runner")
+    gr.Markdown("# Gemini ReAct Agent for GAIA")
     gr.Markdown(
         """
         **Instructions:**
-        1.  This Space is configured to run a Gemini-1.5-Pro based agent.
-        2.  Log in to your Hugging Face account using the button below. Submission is restricted to the Space owner.
-        3.  Click 'Run Evaluation & Submit All Answers' to fetch questions, run the agent, submit answers, and see the score.
-        ---
-        **Note:** The process can take several minutes as the agent answers each question individually.
+        1.  Log in using the Hugging Face login button below.
+        2.  Click 'Run Evaluation & Submit' to start the process.
+        3.  The agent will fetch all 20 questions, reason about them step-by-step, use tools (like web search and a file reader), and submit the final answers for scoring.
+
+        **Note:** This process can take several minutes. Please be patient.
         """
     )
-    # The `gr.LoginButton()` passes the OAuthProfile to any function that accepts it as an argument
     gr.LoginButton()
 
     run_button = gr.Button("Run Evaluation & Submit All Answers")
@@ -149,7 +160,6 @@ with gr.Blocks() as demo:
 
     run_button.click(
         fn=run_and_submit_all,
-        # The profile object from the LoginButton is automatically passed to the first argument of the function
         outputs=[status_output, results_table]
     )