Update app.py

app.py

@@ -3,22 +3,24 @@ import gradio as gr
 import requests
 import inspect
 import pandas as pd
+import json
 from agent import run_agent
 
 # (Keep Constants as is)
 # --- Constants ---
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
+CACHE_FILE = "answers_cache.json"
 
 # --- Basic Agent Definition ---
 # ----- THIS IS WERE YOU CAN BUILD WHAT YOU WANT ------
 class BasicAgent:
     def __init__(self):
         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
+
+        return run_agent(question)
 
 def download_task_file(task_id: str, save_dir: str = "downloads"):
     os.makedirs(save_dir, exist_ok=True)
@@ -43,6 +45,20 @@ def download_task_file(task_id: str, save_dir: str = "downloads"):
     
     return None
 
+# --- Cache helper ---
+def load_cache():
+    if os.path.exists(CACHE_FILE):
+        try:
+            with open(CACHE_FILE, "r") as f:
+                return json.load(f)
+        except Exception:
+            return {}
+    return {}
+
+def save_cache(cache_data):
+    with open(CACHE_FILE, "w") as f:
+        json.dump(cache_data, f, indent=4)
+
 def run_and_submit_all( profile: gr.OAuthProfile | None):
     """
     Fetches all questions, runs the BasicAgent on them, submits all answers,
@@ -62,6 +78,9 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
     questions_url = f"{api_url}/questions"
     submit_url = f"{api_url}/submit"
 
+    # load existing progress
+    answer_cache = load_cache()
+    print(f"Loaded {len(answer_cache)} answers from cache")
     # 1. Instantiate Agent ( modify this part to create your agent)
     try:
         agent = BasicAgent()
@@ -96,30 +115,53 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
     # 3. Run your 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")
         question_text = item.get("question")
+
+        submitted_answer = "NO answer generated"
         
         if not task_id or question_text is None:
             print(f"Skipping item with missing task_id or question: {item}")
             continue
-        try:
-            # try to download the file
-            file_path = download_task_file(task_id)
 
-            if file_path:
-                full_prompt = f"{question_text}\n\n[IMPORTANT] A file associated with this task is located at: {file_path}. Use your tools to read it if necessary."
-            else:
-                full_prompt = question_text
-            
-            submitted_answer = run_agent(full_prompt)
-            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}"})
+        # check cache
+        if task_id in answer_cache:
+            print(f"Task {task_id} found in cache. Skipping generation")
+            submitted_answer = answer_cache[task_id]
+        else:
+            print(f"Task {task_id} not in cache. Running agent...")
+            try:
+                # try to download the file
+                file_path = download_task_file(task_id)
+    
+                if file_path:
+                    full_prompt = f"{question_text}\n\n[IMPORTANT] A file associated with this task is located at: {file_path}. Use your tools to read it if necessary."
+                else:
+                    full_prompt = question_text
+                
+                submitted_answer = run_agent(full_prompt)
+    
+                # update cache
+                answer_cache[task_id] = submitted_answer
+                save_cache(answer_cache)
+
+    
+            except Exception as e:
+                 print(f"Error running agent on task {task_id}: {e}")
+                 submitted_answer = f"AGENT ERROR: {e}"
 
+        # add to payload
+        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,
+            "Source": "Cache" if task_id in answer_cache else "New Run"
+        })
     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)