Update app.py

app.py

@@ -3,6 +3,7 @@ import gradio as gr
 import requests
 import inspect
 import pandas as pd
+from agent import DuckDuckGoAgent
 
 # --- Constants ---
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
@@ -19,8 +20,8 @@ class BasicAgent:
 
 def run_and_submit_all(profile: gr.OAuthProfile | None):
     """
-    Fetches all questions, runs the BasicAgent on them, and prints the results.
-    No submission to external server.
+    Fetches all questions, runs the DuckDuckGoAgent on them, submits all answers,
+    and displays the results.
     """
     # --- Determine HF Space Runtime URL and Repo URL ---
     space_id = os.getenv("SPACE_ID")
@@ -34,14 +35,18 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
 
     api_url = DEFAULT_API_URL
     questions_url = f"{api_url}/questions"
+    submit_url = f"{api_url}/submit"
 
     # 1. Instantiate Agent
     try:
-        agent = BasicAgent()
+        agent = DuckDuckGoAgent()
     except Exception as e:
         print(f"Error instantiating agent: {e}")
         return f"Error initializing agent: {e}", None
 
+    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:
@@ -58,6 +63,7 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
 
     # 3. Run 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")
@@ -67,26 +73,30 @@ 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})
         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 results_log:
-        print("Agent did not produce any answers.")
-        return "Agent did not produce any answers.", pd.DataFrame(results_log)
+    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. Preparar la sumisión 
+    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)
 
-    # 4. Print the Results
-    print(f"Results from running the agent on questions:")
+    # 5. Imprimir los resultados en lugar de enviar
+    print(f"Agent finished. Results (not submitting):")
     for result in results_log:
         print(f"Task ID: {result['Task ID']}")
         print(f"Question: {result['Question']}")
         print(f"Submitted Answer: {result['Submitted Answer']}")
-        print("-" * 50)
-
-    # Returning the results as a DataFrame
+    
     results_df = pd.DataFrame(results_log)
-    return "Evaluation completed. Check the results printed above.", results_df
+    return "Results printed instead of submitted.", results_df
 
 
 # --- Build Gradio Interface using Blocks ---