Update app.py

app.py

@@ -138,11 +138,138 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
         return status_message, results_df
 
 
-def save_fn(profile: gr.OAuthProfile | None):
-    filename = "saved_answers.json"
-    with open(filename, "w") as f:
-        json.dump([], f, indent=2)
-    return f"✅ Saved to {filename}", filename
+import os
+import json
+import requests
+
+def update_and_resubmit_one_answer(task_id_to_redo: str, profile: gr.OAuthProfile | None):
+    """
+    Updates a single answer in saved_answers.json and re-submits the whole payload.
+    """
+
+    # --- Determine HF Space Runtime URL and Repo URL ---
+    space_id = os.getenv("SPACE_ID") # Get the SPACE_ID for sending link to the code
+
+    if profile:
+        username= f"{profile.username}"
+        print(f"User logged in: {username}")
+    else:
+        print("User not logged in.")
+        return "Please Login to Hugging Face with the button.", None
+
+    api_url = DEFAULT_API_URL
+    questions_url = f"{api_url}/questions"
+    submit_url = f"{api_url}/submit"
+
+    # 1. Instantiate Agent ( modify this part to create your agent)
+    try:
+        agent = build_agent()
+    except Exception as e:
+        print(f"Error instantiating agent: {e}")
+        return f"Error initializing agent: {e}", None
+    # In the case of an app running as a hugging Face space, this link points toward your codebase ( usefull for others so please keep it public)
+    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:
+        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 = []
+    with open("saved_answers.json", "r") as f:
+        saved_payload = json.load(f)
+
+    new_payload = []
+    for a in saved_payload:
+        if a["task_id"] != task_id_to_redo:
+            new_payload.append(a)
+
+    print(f"Running agent on 1 question...")
+    for item in questions_data:
+        task_id = item.get("task_id")
+        if task_id == task_id_to_redo:
+            question_text = item.get("question")
+            try:
+                messages = [HumanMessage(content=json.dumps(item))]
+                response = agent.invoke({"messages": messages})
+                submitted_answer = response['messages'][-1].content
+                new_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}"})
+
+    
+    # 4. Prepare Submission 
+    submission_data = {"username": username.strip(), "agent_code": agent_code, "answers": new_payload}
+    status_update = f"Agent finished. Submitting {len(new_payload)} answers for user '{username}'..."
+    print(status_update)
+
+    # Inside run_and_submit_all(), after results_log is built
+    with open("saved_answers.json", "w") as f:
+        json.dump(new_payload, f, indent=2)
+
+    # 5. Submit
+    print(f"Submitting {len(new_payload)} answers to: {submit_url}")
+    try:
+        response = requests.post(submit_url, json=submission_data, timeout=60)
+        response.raise_for_status()
+        result_data = response.json()
+        final_status = (
+            f"Submission Successful!\n"
+            f"User: {result_data.get('username')}\n"
+            f"Overall Score: {result_data.get('score', 'N/A')}% "
+            f"({result_data.get('correct_count', '?')}/{result_data.get('total_attempted', '?')} correct)\n"
+            f"Message: {result_data.get('message', 'No message received.')}"
+        )
+        print("Submission successful.")
+        results_df = pd.DataFrame(results_log)
+        return final_status, results_df
+    except requests.exceptions.HTTPError as e:
+        error_detail = f"Server responded with status {e.response.status_code}."
+        try:
+            error_json = e.response.json()
+            error_detail += f" Detail: {error_json.get('detail', e.response.text)}"
+        except requests.exceptions.JSONDecodeError:
+            error_detail += f" Response: {e.response.text[:500]}"
+        status_message = f"Submission Failed: {error_detail}"
+        print(status_message)
+        results_df = pd.DataFrame(results_log)
+        return status_message, results_df
+    except requests.exceptions.Timeout:
+        status_message = "Submission Failed: The request timed out."
+        print(status_message)
+        results_df = pd.DataFrame(results_log)
+        return status_message, results_df
+    except requests.exceptions.RequestException as e:
+        status_message = f"Submission Failed: Network error - {e}"
+        print(status_message)
+        results_df = pd.DataFrame(results_log)
+        return status_message, results_df
+    except Exception as e:
+        status_message = f"An unexpected error occurred during submission: {e}"
+        print(status_message)
+        results_df = pd.DataFrame(results_log)
+        return status_message, results_df
+
 
 # --- Build Gradio Interface using Blocks ---
 with gr.Blocks() as demo: