Update app.py

app.py

@@ -1,130 +1,93 @@
 import os
-import gradio as gr
-import requests
 import time
+import requests
+import gradio as gr
 import pandas as pd
 
-# --- Constants ---
+GEMINI_API_KEY = os.getenv("GEMINI_API_KEY")
+GEMINI_MODEL = "gemini-1.5-flash"
+GEMINI_API_URL = f"https://generativelanguage.googleapis.com/v1/models/{GEMINI_MODEL}:generateContent"
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 
-# --- Gemini Agent ---
 class GeminiAgent:
     def __init__(self):
-        self.api_key = os.getenv("GEMINI_API_KEY")
-        if not self.api_key:
-            raise ValueError("GEMINI_API_KEY environment variable not set.")
-        self.api_url = f"https://generativelanguage.googleapis.com/v1/models/gemini-1.5-pro:generateContent?key={self.api_key}"
-        print("GeminiAgent initialized.")
+        if not GEMINI_API_KEY:
+            raise ValueError("❌ Переменная окружения GEMINI_API_KEY не установлена.")
 
     def __call__(self, question: str) -> str:
-        headers = {
-            "Content-Type": "application/json"
-        }
+        headers = {"Content-Type": "application/json"}
+        params = {"key": GEMINI_API_KEY}
         payload = {
-            "contents": [{
-                "role": "user",
-                "parts": [{"text": question}]
-            }]
+            "contents": [{"parts": [{"text": question}]}]
         }
 
-        try:
-            response = requests.post(self.api_url, headers=headers, json=payload)
-            if response.status_code == 429:
-                print("Rate limit hit. Waiting 3 seconds before retrying...")
-                time.sleep(3)
-                response = requests.post(self.api_url, headers=headers, json=payload)
+        for attempt in range(3):
+            try:
+                response = requests.post(GEMINI_API_URL, headers=headers, params=params, json=payload)
+                if response.status_code == 429:
+                    print(f"⚠️  Попытка {attempt+1}: Превышен лимит. Ждём 5 сек.")
+                    time.sleep(5)
+                    continue
+                response.raise_for_status()
+                return response.json()["candidates"][0]["content"]["parts"][0]["text"].strip()
+            except Exception as e:
+                print(f"❌ Ошибка: {e}")
+                time.sleep(5)
+        return "Ошибка при получении ответа от Gemini API"
 
-            response.raise_for_status()
-            data = response.json()
-            return data['candidates'][0]['content']['parts'][0]['text']
-        except Exception as e:
-            print(f"Ошибка при вызове Gemini API: {e}")
-            return f"ERROR: {e}"
-
-# --- Evaluation and Submission ---
 def run_and_submit_all(profile: gr.OAuthProfile | None):
     space_id = os.getenv("SPACE_ID")
-    if profile:
-        username = profile.username
-    else:
-        return "Please login with Hugging Face to continue.", None
+    if not profile:
+        return "Пожалуйста, войдите в Hugging Face", None
 
-    questions_url = f"{DEFAULT_API_URL}/questions"
-    submit_url = f"{DEFAULT_API_URL}/submit"
+    username = profile.username
     agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"
+    print(f"Пользователь: {username}")
 
     try:
-        agent = GeminiAgent()
-    except Exception as e:
-        return f"Error initializing agent: {e}", None
-
-    # Fetch questions
-    try:
-        response = requests.get(questions_url, timeout=15)
+        response = requests.get(f"{DEFAULT_API_URL}/questions", timeout=15)
         response.raise_for_status()
         questions_data = response.json()
     except Exception as e:
-        return f"Error fetching questions: {e}", None
+        return f"❌ Ошибка при загрузке вопросов: {e}", None
 
-    # Answer questions
-    answers_payload = []
+    agent = GeminiAgent()
     results_log = []
+    answers_payload = []
 
     for item in questions_data:
         task_id = item.get("task_id")
-        question = item.get("question")
-        if not task_id or question is None:
+        question_text = item.get("question")
+        if not task_id or not question_text:
             continue
-
-        try:
-            answer = agent(question)
-            answers_payload.append({"task_id": task_id, "submitted_answer": answer})
-            results_log.append({"Task ID": task_id, "Question": question, "Submitted Answer": answer})
-        except Exception as e:
-            results_log.append({"Task ID": task_id, "Question": question, "Submitted Answer": f"ERROR: {e}"})
-
-        time.sleep(2)  # ⏳ delay to avoid rate limits
-
-    if not answers_payload:
-        return "Agent did not produce any answers to submit.", pd.DataFrame(results_log)
-
-    # Submit answers
-    submission_data = {
-        "username": username,
-        "agent_code": agent_code,
-        "answers": answers_payload
-    }
+        answer = agent(question_text)
+        results_log.append({"Task ID": task_id, "Question": question_text, "Answer": answer})
+        answers_payload.append({"task_id": task_id, "submitted_answer": answer})
+        time.sleep(3)  # ⏳ Задержка между запросами
 
     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"Score: {result_data.get('score', 'N/A')}% "
-            f"({result_data.get('correct_count')}/{result_data.get('total_attempted')})\n"
-            f"Message: {result_data.get('message')}"
-        )
-        return final_status, pd.DataFrame(results_log)
+        submission_data = {
+            "username": username,
+            "agent_code": agent_code,
+            "answers": answers_payload
+        }
+        submit_response = requests.post(f"{DEFAULT_API_URL}/submit", json=submission_data)
+        submit_response.raise_for_status()
+        result = submit_response.json()
+        score = result.get("score", "N/A")
+        return f"✅ Отправка завершена! Ваш результат: {score}%", pd.DataFrame(results_log)
     except Exception as e:
-        return f"Submission Failed: {e}", pd.DataFrame(results_log)
+        return f"❌ Ошибка при отправке ответов: {e}", pd.DataFrame(results_log)
 
-# --- Gradio UI ---
+# Gradio UI
 with gr.Blocks() as demo:
-    gr.Markdown("## Gemini Agent Evaluation (Unit 4)")
-    gr.Markdown("""
-    1. Убедитесь, что вы установили `GEMINI_API_KEY` как переменную окружения.
-    2. Нажмите кнопку авторизации.
-    3. Нажмите **Run Evaluation** для запуска и отправки.
-    """)
+    gr.Markdown("## Gemini 2.5 Agent 🤖")
+    gr.Markdown("Войдите в Hugging Face и нажмите кнопку для запуска агента.")
     gr.LoginButton()
-    run_btn = gr.Button("Run Evaluation & Submit All Answers")
-    status = gr.Textbox(label="Status")
-    table = gr.DataFrame(label="Answers Log", wrap=True)
-
+    run_btn = gr.Button("▶️ Запустить агента")
+    status = gr.Textbox(label="Статус")
+    table = gr.DataFrame(label="Результаты")
     run_btn.click(fn=run_and_submit_all, outputs=[status, table])
 
 if __name__ == "__main__":
-    print("Launching Gemini Agent Evaluation...")
     demo.launch()