Refactor question fetching logic to support local JSON file or remote API; add JSON import

app.py

@@ -1,3 +1,4 @@
+import json
 import os
 import gradio as gr
 import requests
@@ -13,7 +14,7 @@ from llama_index.tools.duckduckgo import DuckDuckGoSearchToolSpec
 # (Keep Constants as is)
 # --- Constants ---
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
-
+FETCH_QUESTIONS_LOCAL = True
 
 system_prompt="""You are a general AI assistant. I will ask you a question. Report your thoughts, and finish
 your answer with the following template:
@@ -64,25 +65,29 @@ async def run_and_submit_all( profile: gr.OAuthProfile | None):
     print(agent_code)
 
     # 2. Fetch Questions
-    print(f"Fetching questions from: {questions_url}")
-    try:
-        response = requests.get(questions_url, timeout=15)
-        response.raise_for_status()
-        questions_data = response.json()
-        if not questions_data:
-             print("Fetched questions list is empty.")
-             return "Fetched questions list is empty or invalid format.", None
-        print(f"Fetched {len(questions_data)} questions.")
-    except requests.exceptions.RequestException as e:
-        print(f"Error fetching questions: {e}")
-        return f"Error fetching questions: {e}", None
-    except requests.exceptions.JSONDecodeError as e:
-         print(f"Error decoding JSON response from questions endpoint: {e}")
-         print(f"Response text: {response.text[:500]}")
-         return f"Error decoding server response for questions: {e}", None
-    except Exception as e:
-        print(f"An unexpected error occurred fetching questions: {e}")
-        return f"An unexpected error occurred fetching questions: {e}", None
+    if FETCH_QUESTIONS_LOCAL:
+        with open("questions.json", "r") as f:
+            questions_data = json.load(f)
+    else:
+        print(f"Fetching questions from: {questions_url}")
+        try:
+            response = requests.get(questions_url, timeout=15)
+            response.raise_for_status()
+            questions_data = response.json()
+            if not questions_data:
+                print("Fetched questions list is empty.")
+                return "Fetched questions list is empty or invalid format.", None
+            print(f"Fetched {len(questions_data)} questions.")
+        except requests.exceptions.RequestException as e:
+            print(f"Error fetching questions: {e}")
+            return f"Error fetching questions: {e}", None
+        except requests.exceptions.JSONDecodeError as e:
+            print(f"Error decoding JSON response from questions endpoint: {e}")
+            print(f"Response text: {response.text[:500]}")
+            return f"Error decoding server response for questions: {e}", 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 = []