Update app.py

app.py

@@ -2,49 +2,29 @@ import os
 import gradio as gr
 import requests
 import pandas as pd
-import re  # <--- YENİ EKLENEN KISIM: Düzenli ifadeler için gerekli
-from smolagents import CodeAgent, HfApiModel, DuckDuckGoSearchTool, VisitWebpageTool
-# --- Constants ---
-DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
-token = os.getenv("HF_TOKEN")
-model = HfApiModel(model_id="meta-llama/Llama-3.1-70B-Instruct", token=token)
-
-import os
-import gradio as gr
-import requests
-import pandas as pd
-import re
 from smolagents import CodeAgent, HfApiModel, VisitWebpageTool
 
-# --- Constants ---
-DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
+# Model ve Token Ayarları
 token = os.getenv("HF_TOKEN")
 model = HfApiModel(model_id="meta-llama/Llama-3.1-70B-Instruct", token=token)
 
 class AlfredAgent:
     def __init__(self):
-        # --- BASİT VE NET PROMPT ---
-        # Karmaşık kuralları sildik. Modele güveniyoruz.
-        CUSTOM_SYSTEM_PROMPT = """You are a brilliant AI capable of solving complex GAIA benchmark tasks.
+        # SADE VE STANDART PROMPT (Kütüphanenin en iyi anladığı format)
+        CUSTOM_SYSTEM_PROMPT = """You are a helpful and expert AI assistant.
+        Solve the given task by writing Python code. 
+        You have access to a web search tool and a tool to visit webpages.
         
-        You have access to the following tools:
         {{managed_agents_descriptions}}
-        
-        Authorized Python imports:
         {{authorized_imports}}
         
-        INSTRUCTIONS:
-        1. Use 'web_search' to find facts or file contents.
-        2. Use 'visit_webpage' to read detailed articles.
-        3. If you see a file (audio/video/image), search for its filename or context on the web.
-        4. Solve the problem step-by-step using Python code.
-        5. The LAST LINE of your code must evaluate to the final answer (e.g., just the variable name).
-        6. The final answer must be concise (e.g., '14', 'Paris')."""
+        If the task involves a file you cannot see, use web search to find info about it.
+        Always end your script with a variable that contains the final answer."""
 
         self.agent = CodeAgent(
             tools=[VisitWebpageTool()], 
             model=model,
-            max_steps=15, # 15 adım idealdir, fazlası kafasını karıştırıyor
+            max_steps=15, 
             add_base_tools=True,
             additional_authorized_imports=['requests', 'bs4', 'pandas', 'json', 'math', 're', 'datetime'],
             system_prompt=CUSTOM_SYSTEM_PROMPT
@@ -52,274 +32,56 @@ class AlfredAgent:
 
     def __call__(self, question: str) -> str:
         try:
-            # Sadece basit bir yönlendirme
-            result = self.agent.run(f"Question: {question}")
-            ans = str(result).strip()
-            
-            # --- TEMİZLİK ---
-            # Gereksiz karakterleri temizle
-            ans = ans.replace("Final Answer:", "").strip(" .\"'")
-            
-            # Eğer cevap çok uzunsa ve satır satırsa, muhtemelen son satır cevaptır
-            if len(ans) > 50 and "\n" in ans:
-                ans = ans.split('\n')[-1]
-                
-            return ans[:100] # Çok uzun cevapları kırp
+            # Modelin run fonksiyonu zaten en temiz cevabı döndürmeye çalışır
+            result = self.agent.run(question)
+            return str(result).strip()
         except Exception as e:
-            print(f"Agent Error: {e}")
             return "Unknown"
 
-# --- AŞAĞISI STANDART, DEĞİŞTİRMENE GEREK YOK ---
+# --- Gönderim ve Arayüz Fonksiyonu ---
 def run_and_submit_all(profile: gr.OAuthProfile | None):
-    space_id = os.getenv("SPACE_ID")
-    if profile is None:
-        return "Lütfen giriş yapınız.", None
-        
-    username = profile.username
-    print(f"User logged in: {username}")
-
-    api_url = DEFAULT_API_URL
-    questions_url = f"{api_url}/questions"
-    submit_url = f"{api_url}/submit"
-
-    try:
-        agent = AlfredAgent()
-    except Exception as e:
-        return f"Error initializing agent: {e}", None
-
-    agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"
-
-    try:
-        print(f"Fetching questions from: {questions_url}")
-        response = requests.get(questions_url, timeout=15)
-        questions_data = response.json()
-    except Exception as e:
-        return f"Error fetching questions: {e}", None
-
-    results_log = []
-    answers_payload = []
+    if profile is None: return "Giriş gerekli.", None
+    
+    questions_url = "https://agents-course-unit4-scoring.hf.space/questions"
+    submit_url = "https://agents-course-unit4-scoring.hf.space/submit"
+    
+    agent = AlfredAgent()
     
-    for item in questions_data:
-        task_id = item.get("task_id")
-        q_text = item.get("question")
-        if not task_id: continue
-        
-        print(f"\n--- Görev: {task_id} ---")
-        try:
-            answer = agent(q_text)
-            final_ans = str(answer).replace('"', '').replace("'", "").strip()
-            if len(final_ans) > 100: final_ans = final_ans[:100] # Güvenlik önlemi
-            
-            print(f"Bulunan Cevap: {final_ans}")
-            answers_payload.append({"task_id": task_id, "submitted_answer": final_ans})
-            results_log.append({"Task ID": task_id, "Question": q_text, "Submitted Answer": final_ans})
-        except:
-            answers_payload.append({"task_id": task_id, "submitted_answer": "Unknown"})
-
-    submission_data = {"username": username, "agent_code": agent_code, "answers": answers_payload}
-    print(f"Submitting {len(answers_payload)} answers...")
-
-    try:
-        response = requests.post(submit_url, json=submission_data, timeout=60)
-        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)"
-        )
-        return final_status, pd.DataFrame(results_log)
-    except Exception as e:
-        return f"Submission Failed: {e}", pd.DataFrame(results_log)
-
-with gr.Blocks(theme=gr.themes.Soft()) as demo:
-    gr.Markdown("# 🦉 Alfred GAIA Solver - Basit & Güçlü")
-    with gr.Row():
-        with gr.Column(scale=1):
-            gr.LoginButton()
-            run_button = gr.Button("🚀 Başlat", variant="primary")
-        with gr.Column(scale=2):
-            status_output = gr.Textbox(label="Durum", lines=5)
-    results_table = gr.DataFrame(label="Sonuçlar")
-
-    run_button.click(fn=run_and_submit_all, outputs=[status_output, results_table])
-
-if __name__ == "__main__":
-    demo.launch()
-
-def run_and_submit_all( profile: gr.OAuthProfile | None):
-    """
-    Fetches all questions, runs the BasicAgent on them, submits all answers,
-    and displays the results.
-    """
-    # --- 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 = AlfredAgent()
-    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
+    except: return "Sorular alınamadı.", None
 
-    # 3. Run your Agent 
-    results_log = []
     answers_payload = []
+    results_log = []
     
     for item in questions_data:
         task_id = item.get("task_id")
-        q_text = item.get("question")
-        if not task_id: continue
-            
-        print(f"\n--- Görev: {task_id} ---")
-        try:
-            answer = agent(q_text)
-            
-            # Sınav formatına zorla (lowercase ve temizlik)
-            final_ans = str(answer).replace('"', '').replace("'", "").strip()
-            
-            # Eğer model çok uzun bir şey döndürdüyse, GAIA bunu kabul etmez.
-            # İlk 2-3 kelimeyi veya sayıyı almaya çalışalım.
-            if len(final_ans) > 50:
-                final_ans = final_ans[:47] + "..."
-
-            answers_payload.append({"task_id": task_id, "submitted_answer": final_ans})
-            results_log.append({"Task ID": task_id, "Question": q_text, "Submitted Answer": final_ans})
-            print(f"Cevap Kaydedildi: {final_ans}")
-        except:
-            answers_payload.append({"task_id": task_id, "submitted_answer": "Unknown"})
-
-    # 4. Prepare Submission 
-    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)
-
-    # 5. Submit
-    print(f"Submitting {len(answers_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(theme=gr.themes.Soft()) as demo:
-    gr.Markdown("# 🦉 Alfred GAIA Solver - Sertifika Takip Paneli")
-    
-    with gr.Row():
-        with gr.Column(scale=1):
-            gr.LoginButton()
-            # Sadece TEK bir buton tanımlıyoruz
-            run_button = gr.Button("🚀 Sınavı Başlat ve Gönder", variant="primary")
+        answer = agent(item.get("question"))
+        # Temiz ve kısa cevap formatı
+        clean_ans = str(answer).split('\n')[-1].replace("Final Answer:", "").strip(" .\"'")
         
-        with gr.Column(scale=2):
-            # Sadece TEK bir sonuç kutusu
-            status_output = gr.Textbox(label="📊 Güncel Skor ve Durum", lines=5)
+        answers_payload.append({"task_id": task_id, "submitted_answer": clean_ans[:100]})
+        results_log.append({"Task ID": task_id, "Submitted Answer": clean_ans[:100]})
 
-    # Alfred'in ne yaptığını görmek istersen bu kalsın, istemezsen silebilirsin.
-    # Ama şu an fonksiyonumuz 2 çıktı verdiği için bunu 'outputs' listesine eklemiyoruz.
-    agent_logs = gr.Textbox(label="🧠 Alfred'in İşlem Akışı", lines=10, interactive=False, visible=False)
-    
-    # Sadece TEK bir tablo
-    results_table = gr.DataFrame(label="📝 Cevaplanan Sorular")
+    submission_data = {
+        "username": profile.username,
+        "agent_code": f"https://huggingface.co/spaces/{os.getenv('SPACE_ID')}/tree/main",
+        "answers": answers_payload
+    }
 
-    # TEK BİR TIKLAMA OLAYI (Senin fonksiyonun 2 veri döndürdüğü için 2 çıktı yazdık)
-    run_button.click(
-        fn=run_and_submit_all,
-        outputs=[status_output, results_table]
-    )
+    try:
+        res = requests.post(submit_url, json=submission_data, timeout=60).json()
+        return f"Skor: {res.get('score')}% ({res.get('correct_count')}/20)", pd.DataFrame(results_log)
+    except: return "Gönderim başarısız.", pd.DataFrame(results_log)
+
+# Gradio Arayüzü
+with gr.Blocks() as demo:
+    gr.LoginButton()
+    btn = gr.Button("Sınavı Başlat")
+    out = gr.Textbox(label="Sonuç")
+    tab = gr.DataFrame()
+    btn.click(run_and_submit_all, outputs=[out, tab])
 
 if __name__ == "__main__":
-    print("\n" + "-"*30 + " App Starting " + "-"*30)
-    # Check for SPACE_HOST and SPACE_ID at startup for information
-    space_host_startup = os.getenv("SPACE_HOST")
-    space_id_startup = os.getenv("SPACE_ID") # Get SPACE_ID at startup
-
-    if space_host_startup:
-        print(f"✅ SPACE_HOST found: {space_host_startup}")
-        print(f"   Runtime URL should be: https://{space_host_startup}.hf.space")
-    else:
-        print("ℹ️  SPACE_HOST environment variable not found (running locally?).")
-
-    if space_id_startup: # Print repo URLs if SPACE_ID is found
-        print(f"✅ SPACE_ID found: {space_id_startup}")
-        print(f"   Repo URL: https://huggingface.co/spaces/{space_id_startup}")
-        print(f"   Repo Tree URL: https://huggingface.co/spaces/{space_id_startup}/tree/main")
-    else:
-        print("ℹ️  SPACE_ID environment variable not found (running locally?). Repo URL cannot be determined.")
-
-    print("-"*(60 + len(" App Starting ")) + "\n")
-
-    print("Launching Gradio Interface for Basic Agent Evaluation...")
-    demo.launch(debug=True, share=False)
+    demo.launch()