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Update app.py
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app.py
CHANGED
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@@ -1,57 +1,18 @@
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from transformers import AutoModelForCausalLM, AutoTokenizer
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import torch
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import json
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from pathlib import Path
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from datetime import datetime
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import requests
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# === ЗАГРУЗКА МОДЕЛИ ===
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print("🚀 Загрузка модели...")
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model_id = "OpenRussianAI/OpenAirAI-X"
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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model = AutoModelForCausalLM.from_pretrained(model_id)
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device = "cuda" if torch.cuda.is_available() else "cpu"
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model = model.to(device).eval()
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print(f"✅ Модель загружена на {device}")
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# ===
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HISTORY_DIR = Path("chat_history")
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HISTORY_DIR.mkdir(exist_ok=True)
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def get_history_path(username):
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safe_name = "".join(c for c in username if c.isalnum() or c in ('-', '_')).lower()
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return HISTORY_DIR / f"{safe_name}.json"
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def load_history(username):
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path = get_history_path(username)
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if path.exists():
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with open(path, "r", encoding="utf-8") as f:
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return json.load(f)
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return {}
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def save_history(username, history_data):
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path = get_history_path(username)
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with open(path, "w", encoding="utf-8") as f:
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json.dump(history_data, f, ensure_ascii=False, indent=2)
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def check_if_pro(token):
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if not token or not token.startswith("hf_"):
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return False
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try:
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response = requests.get(
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"https://huggingface.co/api/whoami-v2",
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headers={"Authorization": f"Bearer {token}"},
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timeout=5
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)
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if response.status_code == 200:
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data = response.json()
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return data.get("isPro", False) or data.get("plan", {}).get("name") == "PRO"
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except Exception as e:
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print(f"Ошибка проверки PRO: {e}")
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return False
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# === ГЕНЕРАЦИЯ ОТВЕТА ===
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def generate_response(message, history, username, current_chat_id):
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if not username:
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gr.Warning("Сначала введите имя пользователя!")
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@@ -60,8 +21,10 @@ def generate_response(message, history, username, current_chat_id):
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if not message.strip():
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return history, gr.update(), current_chat_id, gr.update()
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history = history + [{"role": "user", "content": message}]
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prompt = ""
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for msg in history:
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if msg["role"] == "user":
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@@ -71,19 +34,37 @@ def generate_response(message, history, username, current_chat_id):
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prompt += "AI:"
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inputs = tokenizer(prompt, return_tensors="pt").to(device)
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with torch.no_grad():
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outputs = model.generate(
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**inputs,
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max_new_tokens=
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temperature=0.7,
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top_p=0.9,
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do_sample=True,
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pad_token_id=tokenizer.eos_token_id
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)
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history = history + [{"role": "assistant", "content": ai_response}]
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if username and current_chat_id:
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@@ -98,237 +79,4 @@ def generate_response(message, history, username, current_chat_id):
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save_history(username, history_data)
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chat_list_choices = get_chat_list(username)
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return history, gr.update(value=""), current_chat_id, gr.update(choices=chat_list_choices)
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# === УПРАВЛЕНИЕ ЧАТАМИ ===
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def new_chat(username):
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if not username:
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return [], None, gr.update(choices=[])
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chat_id = datetime.now().strftime("%Y%m%d_%H%M%S")
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history_data = load_history(username)
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history_data[chat_id] = {
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"title": "Новый чат",
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"created": datetime.now().isoformat(),
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"messages": []
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}
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save_history(username, history_data)
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chat_list_choices = get_chat_list(username)
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return [], chat_id, gr.update(choices=chat_list_choices, value=None)
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def load_chat(chat_title, username, current_chat_id):
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if not username or not chat_title:
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return [], current_chat_id
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history_data = load_history(username)
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for cid, data in history_data.items():
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if data["title"] == chat_title:
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return data["messages"], cid
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return [], current_chat_id
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def get_chat_list(username):
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if not username:
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return []
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history_data = load_history(username)
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sorted_chats = sorted(
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history_data.items(),
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key=lambda x: x[1].get("created", ""),
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reverse=True
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)
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return [data["title"] for _, data in sorted_chats]
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def delete_chat(chat_title, username):
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if not username or not chat_title:
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return [], {}, None, gr.update(choices=[])
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history_data = load_history(username)
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for cid, data in list(history_data.items()):
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if data["title"] == chat_title:
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del history_data[cid]
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break
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save_history(username, history_data)
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chat_list_choices = get_chat_list(username)
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return [], history_data, None, gr.update(choices=chat_list_choices, value=None)
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# === CSS ===
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CUSTOM_CSS = """
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.main-header {
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background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
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color: white;
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padding: 20px;
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border-radius: 12px;
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margin-bottom: 20px;
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text-align: center;
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}
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.main-header h1 { margin: 0; font-size: 2em; }
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.pro-badge {
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background: linear-gradient(135deg, #ffd700 0%, #ffed4e 100%);
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color: #333;
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padding: 4px 12px;
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border-radius: 20px;
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font-weight: bold;
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display: inline-block;
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margin-left: 10px;
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box-shadow: 0 2px 8px rgba(255, 215, 0, 0.4);
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}
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.user-info {
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padding: 10px;
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background: white;
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border-radius: 8px;
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margin-bottom: 10px;
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text-align: center;
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font-weight: 600;
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}
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.privacy-banner {
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background: linear-gradient(135deg, #10b981 0%, #059669 100%);
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color: white;
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padding: 15px 20px;
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border-radius: 10px;
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margin: 15px 0;
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display: flex;
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align-items: center;
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gap: 12px;
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font-size: 0.95em;
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box-shadow: 0 2px 8px rgba(16, 185, 129, 0.3);
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}
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.privacy-banner .icon { font-size: 1.8em; }
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.privacy-banner strong { display: block; font-size: 1.1em; margin-bottom: 4px; }
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"""
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PRIVACY_BANNER = """
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<div class="privacy-banner">
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<div class="icon">🔒</div>
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<div>
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<strong>Ваши данные в безопасности</strong>
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Все сообщения обрабатываются локально.
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<b>Данные НЕ передаются в OpenRussianAI</b>.
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История хранится только внутри контейнера.
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</div>
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</div>
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"""
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# === ИНТЕРФЕЙС ===
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with gr.Blocks(title="OpenAirAI-X Chat") as demo:
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username_state = gr.State("")
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history_state = gr.State({})
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current_chat_id_state = gr.State(None)
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with gr.Column(visible=False) as main_interface:
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gr.HTML("<div class='main-header'><h1>🤖 OpenAirAI-X Chat</h1><p>Русскоязычный AI-ассистент</p></div>")
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gr.HTML(PRIVACY_BANNER)
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with gr.Row():
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with gr.Column(scale=1, min_width=250):
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user_info = gr.Textbox(label="Пользователь", value="Не авторизован", interactive=False, elem_classes="user-info")
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pro_badge = gr.HTML('<div class="pro-badge">👑 PRO</div>', visible=False)
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new_chat_btn = gr.Button("➕ Новый чат", variant="primary")
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gr.Markdown("### 📚 История чатов")
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# Используем Dropdown с allow_custom_value=False для стабильности
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chat_list = gr.Dropdown(choices=[], label="Ваши чаты", interactive=True, allow_custom_value=False, value=None)
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delete_chat_btn = gr.Button("🗑️ Удалить выбранный чат", variant="stop", size="sm")
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logout_btn = gr.Button("🚪 Выйти", size="sm")
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with gr.Column(scale=3):
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chatbot = gr.Chatbot(label="Диалог", height=500)
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with gr.Row():
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msg_input = gr.Textbox(placeholder="Напишите сообщение...", lines=2, scale=5, show_label=False)
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send_btn = gr.Button("📤 Отправить", variant="primary", scale=1)
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with gr.Column(visible=True) as login_screen:
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gr.HTML("<div class='main-header'><h1>🤖 OpenAirAI-X Chat</h1><p>Введите данные для входа</p></div>")
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gr.HTML(PRIVACY_BANNER)
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gr.Markdown("### 🔐 Вход в систему\nВведите ваше имя пользователя. История чатов будет привязана к этому имени.")
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username_input = gr.Textbox(label="Имя пользователя (HF Username)", placeholder="Например: RootLinux21")
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token_input = gr.Textbox(label="HF Token (необязательно, для PRO)", placeholder="hf_...")
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login_btn = gr.Button("🔑 Войти", variant="primary")
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# === ОБРАБОТЧИКИ ===
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def handle_login(username, token):
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if not username.strip():
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gr.Warning("Введите имя пользователя!")
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return gr.update(), gr.update(), "Не авторизован", "", {}, None, gr.update(choices=[], value=None), gr.update(visible=False)
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is_pro = check_if_pro(token)
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history_data = load_history(username)
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chat_list_choices = get_chat_list(username)
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current_chat_id = None
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if not history_data:
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chat_id = datetime.now().strftime("%Y%m%d_%H%M%S")
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history_data[chat_id] = {
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"title": "Новый чат",
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"created": datetime.now().isoformat(),
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"messages": []
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}
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save_history(username, history_data)
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current_chat_id = chat_id
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chat_list_choices = get_chat_list(username)
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pro_badge_html = '<div class="pro-badge">👑 PRO</div>'
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display_name = f"👤 {username}"
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return (
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gr.update(visible=True),
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gr.update(visible=False),
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display_name,
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username,
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history_data,
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current_chat_id,
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gr.update(choices=chat_list_choices, value=None),
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gr.update(visible=is_pro, value=pro_badge_html)
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)
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def handle_logout():
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return (
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gr.update(visible=False),
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gr.update(visible=True),
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"Не авторизован",
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"",
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{},
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None,
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gr.update(choices=[], value=None),
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gr.update(visible=False)
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)
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login_btn.click(
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fn=handle_login,
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inputs=[username_input, token_input],
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outputs=[main_interface, login_screen, user_info, username_state, history_state, current_chat_id_state, chat_list, pro_badge]
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)
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send_btn.click(
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fn=generate_response,
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inputs=[msg_input, chatbot, username_state, current_chat_id_state],
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outputs=[chatbot, msg_input, current_chat_id_state, chat_list]
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)
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msg_input.submit(
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fn=generate_response,
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inputs=[msg_input, chatbot, username_state, current_chat_id_state],
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outputs=[chatbot, msg_input, current_chat_id_state, chat_list]
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)
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new_chat_btn.click(
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fn=new_chat,
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inputs=[username_state],
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outputs=[chatbot, current_chat_id_state, chat_list]
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)
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chat_list.change(
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fn=load_chat,
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inputs=[chat_list, username_state, current_chat_id_state],
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outputs=[chatbot, current_chat_id_state]
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)
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delete_chat_btn.click(
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fn=delete_chat,
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inputs=[chat_list, username_state],
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outputs=[chatbot, history_state, current_chat_id_state, chat_list]
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)
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logout_btn.click(
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fn=handle_logout,
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inputs=None,
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outputs=[main_interface, login_screen, user_info, username_state, history_state, current_chat_id_state, chat_list, pro_badge]
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)
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demo.launch(server_name="0.0.0.0", server_port=7860, css=CUSTOM_CSS)
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# === ЗАГРУЗКА МОДЕЛИ (ИСПРАВЛЕННАЯ ЧАСТЬ) ===
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print("🚀 Загрузка модели...")
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model_id = "OpenRussianAI/OpenAirAI-X"
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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# ВАЖНО: Убеждаемся, что у токенизатора есть pad_token
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if tokenizer.pad_token is None:
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tokenizer.pad_token = tokenizer.eos_token
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model = AutoModelForCausalLM.from_pretrained(model_id)
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device = "cuda" if torch.cuda.is_available() else "cpu"
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model = model.to(device).eval()
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print(f"✅ Модель загружена на {device}")
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# === ГЕНЕРАЦИЯ ОТВЕТА (ПОЛНОСТЬЮ ПЕРЕПИСАННАЯ) ===
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| 16 |
def generate_response(message, history, username, current_chat_id):
|
| 17 |
if not username:
|
| 18 |
gr.Warning("Сначала введите имя пользователя!")
|
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|
| 21 |
if not message.strip():
|
| 22 |
return history, gr.update(), current_chat_id, gr.update()
|
| 23 |
|
| 24 |
+
# Добавляем сообщение пользователя в историю
|
| 25 |
history = history + [{"role": "user", "content": message}]
|
| 26 |
|
| 27 |
+
# Формируем промпт
|
| 28 |
prompt = ""
|
| 29 |
for msg in history:
|
| 30 |
if msg["role"] == "user":
|
|
|
|
| 34 |
prompt += "AI:"
|
| 35 |
|
| 36 |
inputs = tokenizer(prompt, return_tensors="pt").to(device)
|
| 37 |
+
|
| 38 |
with torch.no_grad():
|
| 39 |
outputs = model.generate(
|
| 40 |
**inputs,
|
| 41 |
+
max_new_tokens=128, # Уменьшим, чтобы модель не уходила в бред
|
| 42 |
temperature=0.7,
|
| 43 |
top_p=0.9,
|
| 44 |
do_sample=True,
|
| 45 |
+
pad_token_id=tokenizer.eos_token_id,
|
| 46 |
+
eos_token_id=tokenizer.eos_token_id, # Важно!
|
| 47 |
+
repetition_penalty=1.2 # Штраф за повторения, чтобы убрать цикл "Я OpenAI"
|
| 48 |
)
|
| 49 |
|
| 50 |
+
# Декодируем только НОВУЮ часть текста
|
| 51 |
+
generated_ids = outputs[0][inputs.input_ids.shape[-1]:]
|
| 52 |
+
response_text = tokenizer.decode(generated_ids, skip_special_tokens=True)
|
| 53 |
+
|
| 54 |
+
# Очистка от мусора и обрезка
|
| 55 |
+
# Обычно модель может начать ответ с пробела или новой строки
|
| 56 |
+
ai_response = response_text.strip()
|
| 57 |
|
| 58 |
+
# Если модель все же написала "Пользователь:" или "AI:" в конце, обрезаем
|
| 59 |
+
stop_words = ["Пользователь:", "User:", "\n\n"]
|
| 60 |
+
for stop_word in stop_words:
|
| 61 |
+
if stop_word in ai_response:
|
| 62 |
+
ai_response = ai_response.split(stop_word)[0].strip()
|
| 63 |
+
|
| 64 |
+
# Если ответ пустой после очистки
|
| 65 |
+
if not ai_response:
|
| 66 |
+
ai_response = "..."
|
| 67 |
+
|
| 68 |
history = history + [{"role": "assistant", "content": ai_response}]
|
| 69 |
|
| 70 |
if username and current_chat_id:
|
|
|
|
| 79 |
save_history(username, history_data)
|
| 80 |
|
| 81 |
chat_list_choices = get_chat_list(username)
|
| 82 |
+
return history, gr.update(value=""), current_chat_id, gr.update(choices=chat_list_choices)
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